GRAPHICS SYSTEM WITH VARIABLE RESOLUTION SUPER-SAMPLING

Abstract: A method and computer graphics system capable of super-sampling and performing real-time convolution are disclosed. In one embodiment, the computer graphics system may comprise a graphics processor, a sample buffer, and a sample-to-pixel calculation unit. The graphics processor may be configured to generate a plurality of samples. The sample buffer, which is coupled to the graphics processor, may be configured to store the samples. The sample-to-pixel calculation unit is programmable to select a variable number of stored samples from the sample buffer to filter into an output pixel. The sample-to-pixel calculation unit performs the filter process in real-time, and may use a number of different filter types in a single frame. The sample buffer may be super-sampled, and the samples may be positioned according to a regular grid, a perturbed regular grid, or a stochastic grid.

Description: TITLE: GRAPHICS SYSTEM WITH VARIABLE RESOLUTION SUPER-SAMPLING BACKGROUND OF THE INVENTION 1 Field of the Invention This mvention relates generally to the field of computer graphics and, more particularly, to high performance graphics systems. 2 Descnption of the Related Art A computer system typically relies upon its graphics system for producmg visual output on the computer screen or display device. Early graphics systems were only responsible for taking what the processor produced as output and displaying it on the screen In essence, they acted as simple translators or interfaces. Modern graphics systems, however, incorporate graphics processors with a great deal of processmg power They now act more like coprocessors rather than simple translators This change is due to the recent increase in both the complexity and amount of data bemg sent to the display device For example, modern computer displays have many more pixels, greater color depth, and are able to display more complex images with higher refresh rates than earlier models. Similarly, the images displayed are now more complex and may involve advanced techniques such as antialiasing and texture mapping As a result, without considerable processing power in the graphics system, the CPU would spend a great deal of time performmg graphics calculations This could rob the computer system of the processing power needed for performing other tasks associated with program execution and thereby dramatically reduce overall system performance. With a powerful graphics system, however, when the CPU is instructed to draw a box on the screen, the CPU is freed from havmg to compute the position and color of each pixel. Instead, the CPU may send a request to the video card stating "draw a box at these coordinates " The graphics system then draws the box, freeing the processor to perform other tasks Generally, a graphics system in a computer (also referred to as a graphics system) is a type of video adapter that contains its own processor to boost performance levels. These processors are specialized for computing graphical transformations, so they tend to achieve better results than the general-purpose CPU used by the computer system. In addition, they free up the computer's CPU to execute other commands while the graphics system is handling graphics computations. The popularity of graphical applications, and especially multimedia applications, has made high performance graphics systems a common feature of computer systems. Most computer manufacturers now bundle a high performance graphics system with their systems Since graphics systems typically perform only a limited set of functions, they may be customized and therefore far more efficient at graphics operations than the computer's general-purpose central processor While early graphics systems were limited to performing two-dimensional (2D) graphics, their functionality has mcreased to support three-dimensional (3D) wire-frame graphics, 3D solids, and now includes support for three- dimensional (3D) graphics with textures and special effects such as advanced shading, fogging, alpha-blending, and specular highlighting. The processmg power of 3D graphics systems has been improving at a breakneck pace A few years ago, shaded images of simple objects could only be rendered at a few frames per second, while today's systems support rendering of complex objects at 60Hz or higher. At this rate of mcrease, m the not too distant future, 1 graphics systems will literally be able to render more pixels than a smgle human's visual system can perceive. While this extra performance may be useable in multiple-viewer environments, it may be wasted in more common primarily single-viewer environments Thus, a graphics system is desired which is capable of matching the variable nature of the human resolution system (i.e., capable of putting the quality where it is needed or most perceivable) While the number of pixels is an important factor in determining graphics system performance, another factor of equal import is the quality of the image. For example, an image with a high pixel density may still appear unrealistic if edges within the image are too sharp or jagged (also referred to as "aliased"). One well- known technique to overcome these problems is anti-aliasing. Anti-aliasing mvolves smoothing the edges of objects by shading pixels along the borders of graphical elements. More specifically, anti-aliasing entails removmg higher frequency components from an image before they cause disturbing visual artifacts. For example, anti-aliasing may soften or smooth high contrast edges m an image by forcmg certain pixels to intermediate values (e.g., around the silhouette of a bright object superimposed against a dark background). Another visual effect used to mcrease the realism of computer images is alpha blending Alpha blending is a technique that controls the transparency of an object, allowmg realistic rendeimg of translucent surfaces such as water or glass. Another effect used to improve realism is foggmg Foggmg obscures an object as it moves away from the viewer Simple fogging is a special case of alpha blending m which the degree of alpha changes with distance so that the object appears to vanish mto a haze as the object moves away from the viewer This simple fogging may also be referred to as "depth cueing" or atmospheric attenuation, i.e., lowering the contrast of an object so that it appears less promment as it recedes. More complex types of foggmg go beyond a simple lmear function to provide more complex relationships between the level of translucence and an object's distance from the viewer. Current state of the art software systems go even further by utilizing atmospheric models to provide low-lying fog with improved realism While the techniques listed above may dramatically improve the appearance of computer graphics images, they also have certain limitations. In particular, they may introduce their own aberrations and are typically limited by the density of pixels displayed on the display device As a result, a graphics system is desired which is capable of utilizing mcreased performance levels to mcrease not only the number of pixels rendered but also the quality of the image rendered In addition, a graphics system is desired which is capable of utilizing increases m processmg power to improve the results of graphics effects such as anti-aliasing. Pπor art graphics systems have generally fallen short of these goals. Prior art graphics systems use a conventional frame buffer for refreshing pixel/video data on the display. The frame buffer stores rows and columns of pixels that exactly correspond to respective row and column locations on the display. Prior art graphics system render 2D and/or 3D images or objects mto the frame buffer m pixel form, and then read the pixels from the frame buffer durmg a screen refresh to refresh the display. Thus, the frame buffer stores the output pixels that are provided to the display To reduce visual artifacts that may be created by refreshmg the screen at the same time the frame buffer is being updated, most graphics systems' frame buffers are double- buffered. To obtain more realistic images, some pπor art graphics systems have gone further by generatmg more than one sample per pixel. As used herem, the term "sample" refers to calculated color mformation that mdicates the color, depth (z), transparency, and potentially other mformation, of a particular pomt on an object or image For example a sample may compπse the folio wmg component values, a red value, a green value, a blue value, a z value, and an alpha value (e g., representmg the transparency of the sample) A sample may also compπse other information, e.g., a z-depth value, a blur value, an intensity value, bπghter-than-bnght mformation, and an mdicator that the sample consists partially or completely of control mformation rather than color mformation (i.e , "sample control mformation") By calculating more samples than pixels (1 e , super-sampling), a more detailed image is calculated than can be displayed on the display device For example, a graphics system may calculate four samples for each pixel to be output to the display device. After the samples are calculated, they are then combined or filtered to form the pixels that are stored m the frame buffer and then conveyed to the display device Usmg pixels formed m this manner may create a more realistic final image because overly abrupt changes in the image may be smoothed by the filteπng process These pπor art super-sampling systems typically generate a number of samples that are far greater than the number of pixel locations on the display These pπor art systems typically have rendering processors that calculate the samples and store them mto a render buffer Filtering hardware then reads the samples from the render buffer, filters the samples to create pixels, and then stores the pixels in a traditional frame buffer. The traditional frame buffer is typically double-buffered, with one side bemg used for refreshmg the display device while the other side is updated by the filteπng hardware. Once the samples have been filtered, the resulting pixels are stored in a traditional frame buffer that is used to refresh to display device. These systems, however, have generally suffered from limitations imposed by the conventional frame buffer and by the added latency caused by the render buffer and filteπng Therefore, an improved graphics system is desired which mcludes the benefits of pixel super-samplmg while avoiding the drawbacks of the conventional frame buffer SUMMARY OF THE INVENTION The present invention compπses a computer graphics system that utilizes a super-sampled sample buffer and a programmable sample-to-pixel calculation unit for refreshmg the display In one embodiment, the graphics system may have a graphics processor, a super-sampled sample buffer, and a sample-to-pixel calculation unit The graphics processor generates a plurality of samples and stores them mto a sample buffer. The graphics processor preferably generates and stores more than one sample for at least a subset of the pixel locations on the display Thus, the sample buffer is a super-sampled sample buffer which stores a number of samples that, m some embodiments, may be far greater than the number of pixel locations on the display. In other embodiments, the total number of samples may be closer to, equal to, or even less than the total number of pixel locations on the display device, but the samples may be more densely positioned m certain areas and less densely positioned m other areas The sample-to-pixel calculation unit is configured to read the samples from the super-sampled sample buffer and filter or convolve the samples mto respective output pixels, wherem the output pixels are then provided to refresh the display Note as used herem the terms "filter" and "convolve" are used mterchangeably and refer to mathematically manipulating one or more samples to generate a pixel (e g , by averagmg, by applymg a convolution function, by summing, by applymg a filtering function, by weighting the samples and then manipulating them, by applymg a randomized function, etc ). The sample-to-pixel calculation unit selects one or more samples and filters them to generate an output pixel. Note the number of samples selected and or filtered by the sample-to-pixel calculation unit may be one or, m the preferred embodiment, greater than one. In some embodiments, the number of samples used to form each pixel may vary. For example, the underlymg average sample density m the sample buffer may vary, the extent of the filter may vary, or the number of samples for a particular pixel may vary due to stochastic vaπations m the sample density. In some embodiments the number may vary on a per-pixel basis, on a per-scan lme basis, on a per-region basis, on a per- frame basis, or the number may remam constant. The sample-to-pixel calculation unit may access the samples from the super-sampled sample buffer, perform a real-time filteπng operation, and then provide the resulting output pixels to the display m real-time. The graphics system may operate without a conventional frame buffer, i.e., the graphics system does not utilize a conventional frame buffer which stores the actual pixel values that are bemg refreshed on the display. Note some displays may have internal frame buffers, but these are considered an integral part of the display device, not the graphics system. Thus, the sample-to-pixel calculation units may calculate each pixel for each screen refresh on a real time basis. As used herem, the term "real-time" refers to a function that is performed at or near the display device's refresh rate " "On-the-fly" means at, near, or above the human visual system's perception capabilities for motion fusion (how often a picture must be changed to give the illusion of continuous motion) and flicker fusion (how often light intensity must be changed to give the illusion of continuous) These concepts are further descπbed in the book "Spatial Vision" by Russel L De Valois and Karen K. De Valois, Oxford University Press, 1988. The sample-to-pixel calculation unit may be programmed to vary the number of samples used to generate respective output pixels. For example, the number of samples used may vary accordmg to the location of the output pixel, e.g., the distance of the output pixel from a viewer's pomt of foveation As used herem, the term "po t of foveation" refers to a pomt (e.g., on a display screen) on which the center of a viewer's eyes' field of vision is focused. This pomt may move as the viewer's eyes move. For example, the pomt of foveation (which moves as the viewer's eyes move) may be located at the exact center of the display screen when the viewer is focussmg on a small object displayed at the center of the screen. The human visual system has varying levels of acuity, with the highest level of acuity occurring m the vicinity of the foveal pit of the retma. The foveal region receives light from the pomt of foveation and typically accounts for only a few degrees at the center of a human's of field of vision. Thus, to best match the human visual system, the graphics system may, in some embodiments, be configured to detect where the viewer's pomt of foveation is relative to the display device. This allows the graphics system to match the sample density to the human eye's acuity. Thus, more samples (and more processmg power) will be allocated to areas of the display device that will be perceived by the highest acuity regions of the human visual system. Similarly, less samples and processmg power will be devoted to regions that will be perceived by the lower acuity regions of the human visual system. Note however, it is not just the density of rods and cones m the eye that may be matched. Other factors also mfluence the perception of the human visual system, mcludmg the lens system, chromatic aberrations, and the neural pathways to the eye. For the purposes of matchmg computer displays to human retinal perception, the human bram's processmg limits for visual mput provides a useful target that future graphics systems may stπve to match or exceed. This type of graphics system may be implemented m a number of different ways. For example, eye- tracking sensors may be used to determine in what direction the viewer's eyes are directed This may provide data with which to predict where the viewer's pomt of foveation is Typically, head-mounted eye-tracking sensors may use an additional head-tracking sensor Taken together, the eye- and head-tracking sensors can provide useful information about the position and movement of a viewer's pomt of foveation relative to the display device. Even further accuracy may be obtamed usmg two eye-tracking sensors (i.e , one for each of the viewer's eyes). Thus two points of foveation may be detected for each viewer. Furthermore, m some configurations multiple viewers may each have their points of foveation detected. Other configurations may utilize a hand-tracking sensor (e.g., pointing wand or data glove) in combination with head- and or eye-tracking sensors. Another configuration may utilize a head-mounted display with vaπous motion, direction, eye-tracking and or head-tracking sensors. A higher number of samples may be allocated to a region of a predetermined size centered at the calculated pomt of foveation to compensate for inaccuracies m the sensors (i.e , to ensure that the actual pomt of foveation will receive pixels generated from a high sample density). Note as used herem, the term "gaze trackmg unit" refers to any combmation of eye-tracking, head-tracking, hand trackmg, and or body trackmg sensors that provide mformation concerning one or more viewers' points of foveation (there can be two points of foveation for each viewer) Examples of gaze trackmg units may mclude one or more of the following- video cameras, "EMG" sensors that detect electrical currents m muscles, an eye-and-head tracker, an eye tracker, a head tracker, a hand tracker, a data glove, a wand, a data suit, a mouse, a body position sensor, a body position sensmg chair, motion sensors, pressure sensors, acoustic sensors, and infra-red scanners/sensors. In other embodiments, the system may assume that the viewer's pomt of foveation is located at a fixed location near the center of the screen, or at a varying pomt of mterest on the display created by the software application bemg executed. Thus, the graphics system may be configured to utilize a greater number of samples m computing pixel values in areas where the viewers are able to perceive them, and a second lesser number of samples in computing pixel values m other areas where the viewers are not able to perceive them The sample-to-pixel calculation unit, m varying the number of samples used, preferably vanes the extent of the filter (e.g., the radius of the filter if a circularly symmetπcal filter is used) used for generation of respective output pixels, which affects the number of samples used m calculating the output pixel (m addition, the rendering unit could have already varied the sample density). Alternatively, the sample-to-pixel calculation unit may select samples usmg other methods, e g , randomly selecting/discarding samples to vary the number of samples durmg the filteπng process The graphics processor may be similarly configured to vary the density of samples generated or rendered mto the super-sampled sample buffer for different regions of the displayed image. These different sample density regions may be positioned based on the pomt of mterest, cursor position, eye trackmg, head trackmg, etc. In other embodiments, the sample density may be vaπed on a scan lme basis, a per-prxel basis, or a per-frame region basis In some embodiments, the graphics processor is further configurable to vary the positioning of the samples generated For example, the samples may be positioned according to a regular gπd, a perturbed regular gird, or a random distπbution across the image. The sample positions may be stored m one or more sample position memoπes for fast access In one embodiment, the sample positions may be stored as offsets, rather than absolute addresses or coordmates. In one embodiment, the graphics processor is operable to programmatically configure or vary the sample positions on a frame-by-frame basis or within a smgle frame A software program embodied on a computer medium and a method for operatmg a graphics subsystem are also contemplated. In one embodiment, the method compnses first calculating a plurality of sample locations, and then generatmg a sample for each sample pixel location The samples may then be stored (e.g., mto the super-sampled sample buffer) The sample locations may be specified accordmg to any number of positioning or spacmg schemes, e g , a regular gπd, a perturbed regular gπd, or a stochastic gπd The stored samples may then be selected and filtered to form output pixels, which are provided m real time directly to the display without bemg stored m a traditional frame buffer The samples may be selected accordmg to their distance from the center of the convolution kernel (which corresponds to the estimated center of the output pixel) The selected samples may be multiplied by a weightmg factor and summed The output pixel is also normalized (e g , through the use of pre-normalized weightmg factors that are looked up, or by dividing the summed sample values by a calculated or pre-calculated normalization factor) In some embodiments, the selection process, weighting process, and normalization process are each programmable and changeable within each particular frame on a real-time basis BRIEF DESCRIPTION OF THE DRAWINGS The foregomg, as well as other objects, features, and advantages of this mvention may be more completely understood by reference to the following detailed descπption when read together with the accompanymg drawings m which Figure 1 illustrates one embodiment of a computer system that mcludes one embodiment of a graphics system, Figure 2 is a simplified block diagram of the computer system of Figure 1, Figure 3 is a block diagram illustrating more details of one embodiment of the graphics system of Figure 1, Figure 4 is diagram illustrating traditional pixel calculation, Figure 5A is diagram illustrating one embodiment of super-samplmg, Figure 5B is diagram illustrating a random distπbution of samples, Figure 6 is a diagram illustrating details of one embodiment of a graphics system havmg one embodiment of a vaπable resolution super-sampled sample buffer, Figure 7 is a diagram illustrating details of another embodiment of a graphics system havmg one embodiment of a vaπable resolution super-sampled sample buffer, Figure 8 is a diagram illustrating details of three different embodiments of sample positioning schemes, Figure 9 is a diagram illustrating details of one embodiment of a sample positioning scheme, Figure 10 is a diagram illustrating details of another embodiment of a sample positioning scheme, Figure 11 is a diagram illustrating details of method of converting samples to pixels m parallel, Figure 11A is a diagram illustrating more details of the embodiment from Figure 11, Figure 1 IB is a diagram illustrating details of one embodiment of a method for dealmg with boundary conditions, Figure 12 is a flowchart illustrating one embodiment of a method for drawing samples mto a super- sampled sample buffer, Figure 12A is a diagram illustrating one embodiment for coding tπangle vertices, Figure 13 is a diagram illustrating one embodiment of a method for calculating pixels from samples, Figure 14 is a diagram illustrating details of one embodiment of a pixel convolution for an example set of samples, Figure 15 is a diagram illustrating one embodiment of a method for dividing a super-sampled sample buffer mto regions; Figure 16 is a diagram illustrating another embodiment of a method for dividing a super-sampled sample buffer mto regions; Figure 17 is a diagram illustrating yet another embodiment of a method for dividing a super-sampled sample buffer mto regions; Figures 18A-B are diagrams illustrating one embodiment of a graphics system configured to utilize mput from an eye trackmg or head trackmg device; Figures 19A-B are diagrams illustrating one embodiment of a graphics system configured to vary region position accordmg to the position of a cursor or visual object; and Figure 20 is a diagram of one embodiment of a computer network connecting multiple computers. Figure 21 A illustrates an example of one embodiment of a texture map; Figure 2 IB illustrates an example of one embodiment of texture mappmg onto a cube, Figure 21C illustrates an example of texture mappmg onto a sphencal object, Figure 22 illustrates an example of one embodiment of a imp-map; While the mvention is susceptible to vaπous modifications and alternative forms, specific embodiments thereof are shown by way of example m the drawings and will herem be descnbed m detail. It should be understood, however, that the drawings and detailed descπption thereto are not mtended to limit the mvention to the particular form disclosed, but on the contrary, the mtenhon is to cover all modifications, equivalents, and alternatives falling within the spint and scope of the present mvention as defined by the appended claims. DETAILED DESCRIPTION OF SEVERAL EMBODIMENTS Computer System — Figure 1 Referring now to Figure 1, one embodiment of a computer system 80 that mcludes a three-dimensional (3-D) graphics system is shown The 3-D graphics system may be compπsed m any of vaπous systems, mcludmg a computer system, network PC, Internet appliance, a television, mcludmg HDTV systems and interactive television systems, personal digital assistants (PDAs), and other devices which display 2D and or 3D graphics, among others. As shown, the computer system 80 compnses a system unit 82 and a video monitor or display device 84 coupled to the system unit 82. The display device 84 may be any of vanous types of display monitors or devices (e.g., a CRT, LCD, or gas-plasma display) Vaπous mput devices may be connected to the computer system, mcludmg a keyboard 86 and/or a mouse 88, or other mput device (e g , a trackball, digitizer, tablet, six-degree of freedom mput device, head tracker, eye tracker, data glove, body sensors, etc.). Application software may be executed by the computer system 80 to display 3-D graphical objects on display device 84. As descnbed further below, the 3-D graphics system in computer system 80 mcludes a super-sampled sample buffer with a programmable real-time sample-to-pixel calculation unit to improve the quality and realism of images displayed on display device 84. Computer System Block Diagram — Figure 2 Referring now to Figure 2, a simplified block diagram illustrating the computer system of Figure 1 is shown Elements of the computer system that are not necessary for an understanding of the present mvention are not shown for convemence. As shown, the computer system 80 mcludes a central processmg unit (CPU) 102 coupled to a high-speed memory bus or system bus 104 also refened to as the host bus 104 A system memory 106 may also be coupled to high-speed bus 104. Host processor 102 may compπse one or more processors of varying types, e.g., microprocessors, multiprocessors and CPUs. The system memory 106 may compπse any combmation of different types of memory subsystems, mcludmg random access memoπes, (e.g., static random access memoπes or "SRAMs", synchronous dynamic random access memories or "SDRAMs", and Rambus dynamic access memories or "RDRAM", among others) and mass storage devices. The system bus or host bus 104 may compnse one or more communication or host computer buses (for communication between host processors, CPUs, and memory subsystems) as well as specialized subsystem buses. A 3-D graphics system or graphics system 112 accordmg to the present mvention is coupled to the high- speed memory bus 104. The 3-D graphics system 112 may be coupled to the bus 104 by, for example, a crossbar switch or other bus connectivity logic. It is assumed that vaπous other peripheral devices, or other buses, may be connected to the high-speed memory bus 104. It is noted that the 3-D graphics system may be coupled to one or more of the buses m computer system 80 and/or may be coupled to various types of buses. In addition, the 3D graphics system may be coupled to a communication port and thereby directly receive graphics data from an external source, e.g., the Intemet or a network. As shown m the figure, display device 84 is connected to the 3-D graphics system 112 compnsed m the computer system 80. Host CPU 102 may transfer mformation to and from the graphics system 112 accordmg to a programmed input/output (I O) protocol over host bus 104. Alternately, graphics system 112 may access the memory subsystem 106 accordmg to a direct memory access (DMA) protocol or through intelligent bus mastering A graphics application program conforming to an apphcation programming interface (API) such as OpenGL or Java 3D may execute on host CPU 102 and generate commands and data that define a geometπc primitive (graphics data) such as a polygon for output on display device 84. As defined by the particular graphics interface used, these primitives may have separate color properties for the front and back surfaces. Host processor 102 may transfer these graphics data to memory subsystem 106. Thereafter, the host processor 102 may operate to transfer the graphics data to the graphics system 112 over the host bus 104. In another embodiment, the graphics system 112 may read m geometry data arrays over the host bus 104 usmg DMA access cycles. In yet another embodiment, the graphics system 112 may be coupled to the system memory 106 through a direct port, such as the Advanced Graphics Port (AGP) promulgated by Intel Corporation. The graphics system may receive graphics data from any of vaπous sources, mcludmg the host CPU 102 and/or the system memory 106, other memory, or from an external source such as a network, e.g., the Intemet, or from a broadcast medium, e.g., television, or from other sources As will be descnbed below, graphics system 112 may be configured to allow more efficient microcode control, which results m mcreased performance for handlmg of incoming color values conespondmg to the polygons generated by host processor 102. Note while graphics system 112 is depicted as part of computer system 80, graphics system 112 may also be configured as a stand-alone device (e.g , with its own built-in display) Graphics system 112 may also be configured as a smgle chip device or as part of a system-on-a-cmp or a multi-chip module. Graphics System - Figure 3 Referring now to Figure 3, a block diagram illustrating details of one embodiment of graphics system 112 is shown As shown m the figure, graphics system 112 may compnse one or more graphics processors 90, one or more super-sampled sample buffers 162, and one or more sample-to-pixel calculation units 170A-D. Graphics system 112 may also compπse one or more digital-to-analog converters (DACs) 178A-B. Graphics processor 90 may be any suitable type of high performance processor (e.g., specialized graphics processors or calculation units, multimedia processors, DSPs, or general purpose processors) In one embodiment, graphics processor 90 may compnse one or more rendermg units 150A-D. In the embodiment shown, however, graphics processor 90 also compnses one or more control units 140, one or more data memoπes 152A-D, and one or more schedule units 154. Sample buffer 162 may compnses one or more sample memoπes 160A-160N as shown m the figure A. Control Unit Control unit 140 operates as the interface between graphics system 112 and computer system 80 by controlling the transfer of data between graphics system 112 and computer system 80. In embodiments of graphics system 112 that compnse two or more rendermg umts 150A-D, control unit 140 may also divide the stream of data received from computer system 80 mto a correspondmg number of parallel streams that are routed to the individual rendermg units 150A-D. The graphics data may be received from computer system 80 m a compressed form This may advantageously reduce the bandwidth requirements between computer system 80 and graphics system 112. In one embodiment, control unit 140 may be configured to split and route the data stream to rendermg umts 150A-D m compressed form. The graphics data may compnse one or more graphics primitives. As used herem, the term graphics primitive mcludes polygons, parametnc surfaces, splmes, NURBS (non-uniform rational B-splmes), sub-divisions surfaces, fractals, volume primitives, and particle systems These graphics primitives are descnbed in detail m the text book entitled "Computer Graphics: Principles and Practice" by James D. Foley, et al., published by Addison- Wesley Publishing Co., Inc., 1996. Note polygons are referred to throughout this detailed descnption for simplicity, but the embodiments and examples descnbed may also be used with graphics data compnsmg other types of graphics primitives. B. Rendermg Units Rendering units 150A-D (also referred to herem as draw units) are configured to receive graphics mstmctions and data from control unit 140 and then perform a number of functions, dependmg upon the exact implementation. For example, rendenng units 150A-D may be configured to perform decompression (if the data is compressed), transformation, clipping, lighting, texturing, depth cuemg, transparency processmg, set-up, and screen space rendenng of vanous graphics primitives occurring within the graphics data. Each of these features is descnbed separately below. Dependmg upon the type of compressed graphics data received, rendenng units 150A-D may be configured to perform anthmetic decoding, run-length decodmg, Huffman decodmg, and dictionary decodmg (e.g., LZ77, LZSS, LZ78, and LZW) In another embodiment, rendenng umts 150A-D may be configured to decode graphics data that has been compressed usmg geometπc compression. Geometπc compression of 3D graphics data may achieve significant reductions m data size while retaining most of the image quality. Two methods for compressmg and decompressmg 3D geometry are descnbed m U.S. Patent No. 5,793,371, Application Senal No 08/511,294, (filed on August 4, 1995, entitled "Method And Apparatus For Geometric Compression Of Three-Dimensional Graphics Data," Attorney Docket No. 5181-05900) and U.S. Patent Application Serial No. 09/095,777, filed on June 11, 1998, entitled "Compression of Three-Dimensional Geometry Data Representmg a Regularly Tiled Surface Portion of a Graphical Object," Attorney Docket No. 5181-06602). In embodiments of graphics system 112 that support decompression, the graphics data received by each rendermg unit 150 is decompressed mto one or more graphics "primitives" which may then be rendered. The term primitive refers to components of objects that define its shape (e.g., pomts, lines, tnangles, polygons m two or three dimensions, polyhedra, or free-form surfaces m three dimensions) Rendenng units 150 may be any suitable type of high performance processor (e.g., specialized graphics processors or calculation units, multimedia processors, DSPs, or general purpose processors). Transformation refers to manipulating an object and mcludes translating the object (i.e., movmg the object to a different location), scaling the object (i.e., stretching or shrinking), and rotatmg the object (e.g., m three-dimensional space, or "3 -space") Clipping refers to defining the limits of the displayed image (I e., establishing a clipping region, usually a rectangle) and then not rendenng or displaying pixels that fall outside those limits. Lighting refers to calculating the illumination of the objects within the displayed image to determine what color and or bnghtness each individual object will have. Dependmg upon the shadmg algonthm bemg used (e.g , constant, Gourand, or Phong), lighting may be evaluated at a number of different locations. For example, if constant shadmg is used (I e., each pixel of a polygon has the same lighting), then the lighting need only be calculated once per polygon If Gourand shadmg is used, then the lighting is calculated once per vertex Phong shadmg calculates the lighting on a per-pixel basis Set-up refers to mappmg primitives to a three-dimensional viewport. This involves translating and transforming the objects from their onginal "world-coordinate" system to the established viewport's coordmates. This creates the conect perspective for three-dimensional objects displayed on the screen. Screen-space rendenng refers to the calculations performed to actually calculate the data used to generate each pixel that will be displayed. In pnor art systems, each pixel is calculated and then stored m a frame buffer The contents of the frame buffer are then output to the display device to create the final image. In the embodiment of graphics system 112 shown m the figure, however, rendenng units 150A-D calculate "samples" mstead of actual pixel data. This allows rendenng umts 150A-D to "super-sample" or calculate more than one sample per pixel. Super-samplmg is descnbed m greater detail below. Note that rendenng units 150A-B may compnses a number of smaller functional units, e.g., a separate set-up/decompress unit and a lighting unit. More details on super-samplmg are discussed in the following books: "Principles of Digital Image Synthesis" by Andrew Glassner, 1995, Morgan Kaufman Publishing (Volume 1); and "Renderman Companion-" by Steve Upstill, 1990, Addison Wesley Publishing. 10 C. Dat Memones Each rendenng unit 150A-D may be coupled to an instruction and data memory 152A-D. In one embodiment, each data memory 152A-D may be configured to store both data and mstmctions for rendenng umts 150A-D While implementations may vary, m one embodiment each data memory 152A-D may compnse two 8MByte SDRAMs providmg a total of 16 MBytes of storage for each rendenng unit 150A-D. In another embodiment, RDRAMs (Rambus DRAMs) may be used to support the decompression and set-up operations of each rendenng unit, while SDRAMs may be used to support the draw functions of rendenng units 150A-D. P. Schedule Unit Schedule unit 154 may be coupled between the rendenng umts 150A-D and the sample memones 160A- N. Schedule unit 154 is configured to sequence the completed samples and store them m sample memones 160A- N. Note m larger configurations, multiple schedule units 154 may be used m parallel. In one embodiment, schedule unit 154 may be implemented as a crossbar switch. E. Sample Memones Super-sampled sample buffer 162 comprises sample memones 160A-160N, which are configured to store the plurality of samples generated by the rendenng units. As used herem, the term "sample buffer" refers to one or more memones which store samples As previously noted, one or more samples are filtered to form output pixels (i.e., pixels to be displayed on a display device). The number of samples stored may be greater than, equal to, or less than the total number of pixels output to the display device to refresh a smgle frame. Each sample may correspond to one or more output pixels. As used herem, a sample "corresponds" to an output pixel when the sample's mformation contπbutes to final output value of the pixel. Note, however, that some samples may contnbute zero to their correspondmg output pixel after filtering takes place Stated another way, the sample buffer stores a plurality of samples that have positions that coπespond to locations m screen space on the display, i.e., the samples contnbute to one or more output pixels on the display. The number of stored samples may be greater than the number of pixel locations, and more than one sample may be combined m the convolution (filtering) process to generate a particular output pixel displayed on the display device. Any given sample may contnbute to one or more output pixels. Sample memoπes 160A-160N may compnse any of a number of different types of memones (e.g., SDRAMs, SRAMs, RDRAMs, 3DRAMs, or next-generation 3DRAMs) m varymg sizes. In one embodiment, each schedule unit 154 is coupled to four banks of sample memones, wherem each bank compnses four 3DRAM- 64 memones. Together, the 3DRAM-64 memones may form a 116-bit deep super-sampled sample buffer that stores multiple samples per pixel. For example, in one embodiment, each sample memory 160A-160N may store up to sixteen samples per pixel. 3DRAM-64 memoπes are specialized memones configured to support full mtemal double buffering with smgle buffered Z m one chip. The double buffered portion compnses two RGBX buffers, wherem X is a fourth channel that can be used to store other information (e.g., alpha). 3DRAM-64 memones also have a lookup table that takes m wmdow ID information and controls an mtemal 2-1 or 3-1 multiplexer that selects which buffer's contents will be output. 3DRAM-64 memones are next-generation 3DRAM memones that may soon be available from Mitsubishi Electnc Corporation's Semiconductor Group. In one embodiment, four chips used m 11 combmation are sufficient to create a double-buffered 1280 x 1024 super-sampled sample buffer. Smce the memoπes are internally double-buffered, the mput pms for each of the two frame buffers m the double-buffered system are time multiplexed (usmg multiplexers within the memones). The output pms may similarly be time multiplexed. This allows reduced pm count while still providmg the benefits of double buffering 3DRAM-64 memones further reduce p count by not havmg z output pms. Smce z companson and memory buffer selection is dealt with internally, this may simplify sample buffer 162 (e.g., usmg less or no selection logic on the output side). Use of 3DRAM-64 also reduces memory bandwidth smce mformation may be wntten mto the memory without the traditional process of readmg data out, performmg a z companson, and then wnting data back m Instead, the data may be simply wntten mto the 3DRAM-64, with the memory performmg the steps descnbed above internally. However, m other embodiments of graphics system 112, other memones (e.g., SDRAMs, SRAMs, RDRAMs, or current generation 3DRAMs) may be used to form sample buffer 162 Graphics processor 90 may be configured to generate a plurality of sample positions accordmg to a particular sample positioning scheme (e g., a regular gnd, a perturbed regular grid, etc.). Alternatively, the sample positions (or offsets that are added to regular gπd positions to form the sample positions) may be read from a sample position memory (e.g., a RAM/ROM table). Upon receiving a polygon that is to be rendered, graphics processor 90 determines which samples fall within the polygon based upon the sample positions Graphics processor 90 renders the samples that fall within the polygon and stores rendered samples m sample memones 160A-N. Note as used herem the terms render and draw are used mterchangeable and refer to calculating color values for samples Depth values, alpha values, and other per-sample values may also be calculated m the rendenng or drawing process. E. Sample-to-pixel Calculation Umts Sample-to-pixel calculation units 170A-D may be coupled between sample memoπes 160A-N and DACs 178A-B. Sample-to-pixel calculation units 170A-D are configured to read selected samples from sample memones 160A-N and then perform a convolution (e.g., a filtermg and weighting function or a low pass filter) on the samples to generate the output pixel values which are output to DACs 178A-B. The sample-to-pixel calculation units 170A-D may be programmable to allow them to perform different filter functions at different times, dependmg upon the type of output desired. In one embodiment, the sample-to-pixel calculation umts 170A-D may implement a 5x5 super-sample reconstmction band-pass filter to convert the super-sampled sample buffer data (stored m sample memoπes 160A-N) to smgle pixel values. In other embodiments, calculation units 170A-D may filter a selected number of samples to calculate an output pixel. The filtered samples may be multiplied by a vanable weightmg factor that gives more or less weight to samples avmg positions close the center of the pixel bemg calculated. Other filteπng functions may also be used either alone or m combmation, e.g., tent filters, circular and elliptical filters, Mitchell filters, band pass filters, sync function filters, etc. Sample-to-pixel calculation units 170A-D may also be configured with one or more of the following features: color look-up usmg pseudo color tables, direct color, inverse gamma correction, filteπng of samples to pixels, and conversion of pixels to non-lmear light space. Other features of sample-to-pixel calculation umts 170A-D may mclude programmable video timing generators, programmable pixel clock synthesizers, and 12 crossbar functions. Once the sample-to-pixel calculation units have manipulated the timing and color of each pixel, the pixels are output to DACs 178A-B. F. DACs DACs 178A-B operate as the final output stage of graphics system 112. The DACs 178A-B serve to translate the digital pixel data received from cross units 174A-B mto analog video signals that are then sent to the display device. Note in one embodiment DACs 178A-B may be bypassed or omitted completely in order to output digital pixel data m lieu of analog video signals. This may be useful when display device 84 is based on a digital technology (e.g., an LCD-type display or a digital micro-mirror display) Super-Sampling - Figures 4-5 Turning now to Figure 4, an example of traditional, non-super-sampled pixel value calculation is illustrated. Each pixel has exactly one data point calculated for it, and the smgle data pomt is located at the center of the pixel. For example, only one data pomt (i.e , sample 74) contπbutes to value of pixel 70 Turning now to Figure 5 A, an example of one embodiment of super-samplmg is illustrated In this embodiment, a number of samples are calculated The number of samples may be related to the number of pixels or completely mdependent of the number of pixels. In this example, there are 18 samples distnbuted in a regular gnd across nme pixels. Even with all the samples present m the figure, a simple one to one correlation could be made (e g., by throwing out all but the sample nearest to the center of each pixel). However, the more interesting case is performmg a filteπng function on multiple samples to determine the final pixel values. Also, as noted above, a smgle sample can be used to generate a plurality of output pixels, i.e., sub-samplmg. A circular filter 72 is illustrated in the figure. In this example, samples 74A-B both contnbute to the final value of pixel 70. This filtermg process may advantageously improve the realism of the image displayed by smoothing abrupt edges m the displayed image (i.e., performmg anti-aliasing). Filter 72 may simply average samples 74A-B to form the final value of output pixel 70, or it may mcrease the contπbution of sample 74B (at the center of pixel 70) and dimmish the contπbution of sample 74 A (I e., the sample farther away from the center of pixel 70) Circular filter 72 is repositioned for each output pixel bemg calculated so the center of filter 72 comcides with the center position of the pixel bemg calculated. Other filters and filter positioning schemes are also possible and contemplated. Turning now to Figure 5B, another embodiment of super-samplmg is illustrated. In this embodiment, however, the samples are positioned randomly. More specifically, different sample positions are selected and provided to graphics processor 90 (and render units 150A-D), which calculate color mformation to form samples at these different locations. Thus the number of samples falling within filter 72 may vary from pixel to pixel. Super-Sampled Sample buffer with Real-Time Convolution — Figures 6-13 Turning now to Figure 6, a diagram illustrating one possible configuration for the flow of data through one embodiment of graphics system 112 is shown. As the figure shows, geometry data 350 is received by graphics system 112 and used to perform draw process 352. The draw process 352 is implemented by one or more of control umt 140, rendenng units 150, memones 152, and schedule unit 154. Geometry data 350 compnses data for one or more polygons. Each polygon compnses a plurality of vertices (e.g., three vertices m 13 the case of a tnangle), some of which may be shared. Data such as x, y, and z coordmates, color data, lighting data and texture map mformation may be included for each vertex. In addition to the vertex data, draw process 352 (which may be performed by rendenng units 150A-D) also receives sample coordmates from a sample position memory 354. In one embodiment, position memory 354 is embodied within rendenng units 150A-D In another embodiment, position memory 354 may be realized as part of texture and render memones 152A-152D, or as a separate memory. Sample position memory 354 is configured to store position mformation for samples that are calculated m draw process 352 and then stored mto super-sampled sample buffer 162. In one embodiment, position memory 354 may be configured to store entire sample addresses. However, this may mvolve mcreasmg the size of position memory 354 Alternatively, position memory 354 may be configured to store only x- and y-offsets for the samples. Stonng only the offsets may use less storage space than stonng each sample's entire position. The offsets may be relative to bm coordmates or relative to positions on a regular gπd. The sample position mformation stored m sample position memory 354 may be read by a dedicated sample position calculation unit (not shown) and processed to calculate example sample positions for graphics processor 90. More detailed mformation on sample position offsets is mcluded below (see descπption of Figures 9 and 10) In another embodiment, sample position memory 354 may be configured to store a table of random numbers Sample position memory 354 may also compnse dedicated hardware to generate one or more different types of regular gnds This hardware may be programmable. The stored random numbers may be added as offsets to the regular gnd positions generated by the hardware. In one embodiment, the sample position memory may be programmable to access or "unfold" the random number table m a number of different ways. This may allow a smaller table to be used without visual artifacts caused by repeating sample position offsets. In one embodiment, the random numbers may be repeatable, thereby allowmg draw process 352 and sample-to-pixel calculation process 360 to utilize the same offset for the same sample without necessanly stonng each offset. As shown m the figure, sample position memory 354 may be configured to store sample offsets generated accordmg to a number of different schemes such as a regular square gnd, a regular hexagonal gnd, a perturbed regular grid, or a random (stochastic) distnbution. Graphics system 112 may receive an indication from the operatmg system, device dnver, or the geometry data 350 that mdicates which type of sample positioning scheme is to be used. Thus the sample position memory 354 is configurable or programmable to generate position information accordmg to one or more different schemes. More detailed mformation on several sample position schemes are descnbed further below (see descnption of Figure 8) In one embodiment, sample position memory 354 may compπse a RAM/ROM that contams stochastic sample pomts (or locations) for different total sample counts per bm. As used herem, the term "bin" refers to a region or area in screen-space and contams however many samples are m that area (e.g., the bm may be lxl pixels in area, 2x2 pixels m area, etc.). The use of bins may simplify the storage and access of samples m sample buffer 162. A number of different bm sizes may be used (e.g., one sample per bm, four samples per bm, etc.). In the preferred embodiment, each bm has an xy-position that corresponds to a particular location on the display. The bins are preferably regularly spaced. In this embodiment the bins' xy-positions may be determined from the bm's storage location within sample buffer 162. The bins' positions correspond to particular positions on the display. In some embodiments, the bm positions may conespond to pixel centers, while m other embodiments the bm positions correspond to pomts that are located between pixel centers. The specific position of each sample within 14 a bm may be determined by lookmg up the sample's offset m the RAM ROM table (the offsets may be stored relative to the correspondmg b position). However, dependmg upon the implementation, not all bm sizes may have a unique RAM/ROM entry. Some bm sizes may simply read a subset of the larger bm sizes' entnes. In one embodiment, each supported size has at least four different sample position scheme vaπants, which may reduce final image artifacts due to repeatmg sample positions. In one embodiment, position memory 354 may store parrs of 8-bit numbers, each pan: compnsmg an x- offset and a y-offset (other possible offsets are also possible, e.g., a time offset, a z-offset, etc.). When added to a bm position, each pair defines a particular position m screen space. The term "screen space" refers generally to the coordinate system of the display device. To improve read times, memory 354 may be constructed in a wide/parallel manner so as to allow the memory to output more than one sample location per clock cycle. Once the sample positions have been read from sample position memory 354, draw process 352 selects the samples positions that fall withm the polygon currently bemg rendered. Draw process 352 then calculates the z and color mformation (which may mclude alpha or other depth of field mformation values) for each of these samples and stores the data mto sample buffer 162. In one embodiment, the sample buffer may only single-buffer z values (and perhaps alpha values) while double buffering other sample components such as color. Unlike pπor art systems, graphics system 112 may double buffer all samples (although not all sample components may be double-buffered, i.e., the samples may have components that are not double-buffered, or not all samples may be double-buffered). In one embodiment, the samples are stored mto sample buffer 162 in bms. In some embodiments, the size of bms, i.e., the quantity of samples withm a bm, may vary from frame to frame and may also vary across different regions of display device 84 withm a smgle frame. For example, bms along the edges of display device may compπse only one sample, while bms correspondmg to pixels near the center of display device 84 may compnse sixteen samples. Note the area of bms may vary from region to region. The use of bms will be descnbed in greater detail below m connection with Figure 11. In parallel and mdependently of draw process 352, filter process 360 is configured to read samples from sample buffer 162, filter (i.e , filter) them, and then output the resulting output pixel to display device 84 Sample-to-pixel calculation units 170 implement filter process 380 Thus, for at least a subset of the output pixels, the filter process is operable to filter a plurality of samples to produce a respective output pixel. In one embodiment, filter process 360 is configured to- (I) determine the distance from each sample to the center of the output pixel bemg filtered, (n) multiply the sample's components (e.g., color and alpha) with a filter value that is a specific (programmable) function of the distance; (in) sum all the weighted samples that contnbute to the output pixel, and (IV) normalize the resulting output pixel. The filter process 360 is descnbed m greater detail below (see descnption accompanying Figures 11, 12, and 14). Note the extent of the filter need not be circular (i.e., it may be a function of x and y mstead of the distance), but even if the extent is, the filter need not be circularly symmetπcal. The filter's "extent" is the area withm which samples can mfluence the particular pixel bemg calculated with the filter. Turning now to Figure 7, a diagram illustrating an alternate embodiment of graphics system 112 is shown. In this embodiment, two or more sample position memones 354A and 354B are utilized. Thus, the sample position memoπes 354A-B are essentially double-buffered. If the sample positions are kept the same from frame to frame, then the sample positions may be smgle buffered. However, if the sample positions may vary from frame to frame, then graphics system 112 may be advantageously configured to double-buffer the sample 15 positions. The sample positions may be double buffered on the rendermg side (i.e., memory 354A may be double buffered) and or the filter/convolve side (i.e., memory 354B may be double buffered). Other combinations are also possible. For example, memory 354A may be smgle-buffered, while memory 354B is doubled buffered. This configuration may allow one side of memory 354B to be used for refreshmg (i.e., by filter/convolve process 360) while the other side of memory 354B is used bemg updated. In this configuration, graphics system 112 may change sample position schemes on a per-frame basis by shiftmg the sample positions (or offsets) from memory 354A to double-buffered memory 354B as each frame is rendered. Thus, the positions used to calculate the samples (read from memory 354A) are copied to memory 354B for use durmg the filtenng process (i.e., the sample-to-pixel conversion process). Once the position mformation has been copied to memory 354B, position memory 354 A may then be loaded with new sample position offsets to be used for the second frame to be rendered. In this way the sample position mformation follows the samples from the draw/render process to the filter process. Yet another alternative embodiment may store tags to offsets with the samples themselves in super- sampled sample buffer 162. These tags may be used to look-up the offset/perturbation associated with each particular sample Sample Positioning Schemes Figure 8 illustrates a number of different sample positioning schemes. In regular gπd positioning scheme 190, each sample is positioned at an mtersection of a regularly-spaced gπd. Note however, that as used herem the term "regular gnd" is not limited to square gπds. Other types of gπds are also considered "regular" as the term is used herem, mcludmg, but not limited to, rectangular gπds, hexagonal gnds, tnangular gnds, loganthmic gπds, and semi-regular lattices such as Penrose tiling Perturbed regular gπd positioning scheme 192 is based upon the previous definition of a regular gnd. However, the samples m perturbed regular grid scheme 192 may be offset from their correspondmg gnd mtersection. In one embodiment, the samples may be offset by a random angle (e.g., from 0° to 360°) and a random distance, or by random x and y offsets, which may or may not be limited to a predetermined range. The offsets may be generated in a number of ways, e.g , by hardware based upon a small number of seeds, looked up from a table, or by usmg a pseudo-random function Once agam, perturbed regular gird scheme 192 may be based on any type of regular gnd (e.g., square, or hexagonal). A rectangular or hexagonal perturbed grid may be particularly desirable due to the geometnc properties of these gnd types. Stochastic sample positioning scheme 194 represents a third potential type of scheme for positioning samples. Stochastic sample positioning involves randomly distnbuting the samples across a region (e.g., the displayed region on a display device or a particular wmdow). Random positioning of samples may be accomplished through a number of different methods, e.g., usmg a random number generator such as an mtemal clock to generate pseudo-random numbers. Random numbers or positions may also be pre-calculated and stored m memory. Turning now to Figure 9, details of one embodiment of perturbed regular gnd scheme 192 are shown. In this embodiment, samples are randomly offset from a regular square gnd by x- and y-offsets. As the enlarged area shows, sample 198 has an x-offset 134 that specifies its horizontal displacement from its correspondmg gnd mtersection pomt 196. Similarly, sample 198 also has a y-offset 136 that specifies its vertical displacement from 16 gnd mtersection pomt 196. The random offset may also be specified by an angle and distance. As with the previously disclosed embodiment that utilized angles and distances, x-offset 134 and y-offset 136 may be limited to a particular minimum and or maximum value or range of values. Turning now to Figure 10, details of another embodiment of perturbed regular gnd scheme 192 are shown. In this embodiment, the samples are grouped mto "bms" 138A-D. In this embodiment, each bm compnses nine (i.e., 3 x 3) samples. Different bm sizes may be used in other embodiments (e.g., bms stonng 2 x 2 samples or 4 x 4 samples). In the embodiment shown, each sample's position is determined as an offset relative to the position of the bm. The position of the bms may be defined as any convenient position related to the gπd, e.g., the lower left-hand comers 132A-D as shown in the figure. For example, the position of sample 198 is determined by summing x-offset 124 and y-offset 126 to the x and y coordmates of the comer 132D of bm 138D As previously noted, this may reduce the size of the sample position memory used m some embodiments Turning now to Figure 11, one possible method for rapidly converting samples stored m sample buffer 162 mto pixels is shown. In this embodiment, the contents of sample buffer 162 are organized mto columns (e.g., Cols. 1-4). Each column m sample buffer 162 may compnse a two-dimensional anay of bms The columns may be configured to horizontally overlap (e g., by one or more bms), and each column may be assigned to a particular sample-to-pixel calculation unit 170A-D for the convolution process. The amount of the overlap may depend upon the extent of the filter bemg used. The example shown m the figure illustrates an overlap of two bms (each square such as square 188 represents a smgle bm compnsmg one or more samples). Advantageously, this configuration may allow sample-to-pixel calculation units 170A-D to work independently and m parallel, with each sample-to-pixel calculation unit 170A-D receivmg and convertmg its own column. Overlappmg the columns will eliminate visual bands or other artifacts appearmg at the column boundaries for any operators larger than a pixel m extent. Turning now to Figure 11 A, more details of one embodiment of a method for readmg the samples from a super-sampled sample buffer are shown. As the figure illustrates, the convolution filter kernel 400 travels across column 414 (see arrow 406) to generate output pixels. One or more sample-to-pixel calculation units 170 may implement the convolution filter kernel 400 A bm cache 408 may used to provide quick access to the samples that may potentially contnbute to the output pixel. As the convolution process proceeds, bms are read from the super-sampled sample buffer and stored in bm cache 408. In one embodiment, bms that are no longer needed 410 are overwritten m the cache by new bms 412. As each pixel is generated, convolution filter kernel 400 shifts. Kernel 400 may be visualized as proceeding m a sequential fashion withm the column m the dnection mdicated by arrow 406. When kernel 400 reaches the end of the column, it may shift down one or more rows of samples and then proceed agam. Thus the convolution process proceeds m a scan lme manner, generalmg one column of output pixels for display. Turning now to Figure 1 IB, a diagram illustrating potential border conditions is shown. In one embodiment, the bms that fall outside of sample wmdow 420 may be replaced with samples havmg predetermmed background colors specified by the user. In another embodiment, bms that fall outside the wmdow are not used by setting their weighting factors to zero (and then dynamically calculating normalization coefficients). In yet another embodiment, the bms at the mside edge of the wmdow may be duplicated to replace those outside the wmdow. This is mdicated by outside bm 430 bemg replaced by mirror mside bm 432. 17 Figure 12 is a flowchart of one embodiment of a method for drawing or rendenng sample pixels mto a super-sampled sample buffer. Certain of the steps of Figure 12 may occur concurrently or m different orders. In this embodiment, the graphics system receives graphics commands and graphics data from the host CPU 102 or directly from mam memory 106 (step 200). Next, the mstmctions and data are routed to one or more rendenng units 150A-D (step 202). If the graphics data is compressed (step 204), then the rendenng units 150A-D decompress the data mto a useable format, e.g., tπangles (step 206). Next, the tπangles are processed, e.g., converted to screen space, lit, and transformed (step 208 A) If the graphics system implements vanable resolution super samplmg, then the tnangles are compared with the sample density region boundaπes (step 208B). In vanable-resolution super-sampled sample buffer implementations, different regions of the display device may be allocated different sample densities based upon a number of factors (e.g., the center of the attention on the screen as determined by eye or head trackmg). Sample density regions are descnbed m greater detail below (see section entitled Vanable Resolution Sample buffer below). If the tnangle crosses a region boundary (step 210), then the tnangle may be divided mto two smaller polygons along the region boundary (step 212). This may allow each newly formed tnangle to have a smgle sample density In one embodiment, the graphics system may be configured to simply use the entire tnangle twice (i.e., once m each region) and then use a boundmg box to effectively clip the tnangle. Next, one of the sample position schemes (e g , regular gπd, perturbed regular grid, or stochastic) are selected from the sample position memory 184 (step 214). The sample position scheme will generally have been pre-programmed mto the sample position memory 184, but may also be selected "on the fly". Based upon this sample position scheme and the sample density of the region containing the tnangle, rendenng units 150A-D determine which bms may contain samples located withm the tnangle's boundanes (step 216). The offsets for the samples withm these bms are then read from sample position memory 184 (step 218). Each sample's position is then calculated usmg the offsets and is compared with the triangle's vertices to determine if the sample is withm the tnangle (step 220). Step 220 is discussed m greater detail below For each sample that is determined to be withm the tnangle, the rendenng unit draws the sample by calculating the sample's color, alpha and other attributes. This may mvolve lighting calculation and interpolation based upon the color and texture map mformation associated with the vertices of the tnangle Once the sample is rendered, it may be forwarded to schedule unit 154, which then stores the sample m sample buffer 162 (step 224). Note the embodiment of the method descnbed above is used for explanatory purposes only and is not meant to be limiting. For example, m some embodiments the steps shown m the figure as occurring seπally may be implemented m parallel. Furthermore, some steps may be reduced or eliminated m certain embodiments of the graphics system (e.g., steps 204-206 m embodiments that do not implement geometry compression or steps 210- 212 m embodiments that do not implement a vanable resolution super-sampled sample buffer). Determination of Which Samples Reside Within the Polygon Being Rendered The companson may be performed m a number of different ways. In one embodiment, the deltas between the three vertices defining the tnangle are first determined. For example, these deltas may be taken m the order of first to second vertex (v2 - vl)=dl2, second to third vertex (v3 - v2)=d23, and third vertex back to the first vertex (v 1 - v3 )=d31. These deltas form vectors, and each vector may be categorized as belongmg to one of the four quadrants of the coordmate plane (e.g., by usmg the two sign bits of its delta X and Y coefficients). A 18 third condition may be added determining whether the vector is an X-major vector or Y-major vector. This may be determined by calculating whether abs(delta x) is greater than abs(delta_y) Usmg these three bits of information, the vectors may each be categorized as belongmg to one of eight different regions of the coordmate plane. If three bits are used to define these regions, then the X-sign bit (shifted left by two), the Y-sign bit (shifted left by one), and the X-major bit, may be used to create the eight regions as shown in Figure 12A Next, three edge equations may be used to define the mside portion of the tnangle. These edge equations (or half-plane equations) may be defined usmg slope-mtercept form To reduce the numencal range needed, both X-major and Y-major equation forms may be used (such that the absolute value of the slope value may be m the range of 0 to 1). Thus, the two edge equations are: X-major y-m-x-b < 0, when the point is below the lme Y-major: x-m-y-b < 0, when the pomt is to the left of the lme The X-major equations produces a negative versus positive value when the pomt m question is below the lme, while the Y-major equation produces a negative versus positive value when the pomt m question is to the left of the lme. Since which side of the lme is the "accept" side is known, the sign bit (or the mverse of the sign bit) of the edge equation result may be used to determine whether the sample is on the "accept" side or not This is refened to herem as the "accept bit". Thus, a sample is on the accept side of a lme if. X-major (y-m-x-b<0) <xor> accept Y-major: (x-m-y-bO) <xor> accept The accept bit may be calculated accordmg to the following table, wherem cw designates whether the tnangle is clockwise (cw = 1) or counter -clockwise (cw=0) 1- accept = 'cw 0: accept = cw 4- accept = cw 5: accept = cw 7: accept = cw 6: accept = !cw 2: accept = !cw 3: accept = !cw Tie breakmg rules for this representation may also be implemented (e.g., coordmate axes may be defined as belongmg to the positive octant). Similarly, X-major may be defined as owning all pomts that tie on the slopes. In an alternate embodiment, the accept side of an edge may be determined by applymg the edge equation to the third vertex of the tnangle (the vertex that is not one of the two vertices forming the edge). This method may incur the additional cost of a multiply-add, which may not be used by the technique descnbed above 19 To detemune the "faced-ness" of a tnangle (1 e., whether the tnangle is clockwise or counter-clockwise), the delta-directions of two edges of the tnangle may be checked and the slopes of the two edges may be compared. For example, assuming that edgel2 has a delta-direction of 1 and the second edge (edge23) has a delta-direction of 0, 4, or 5, then the tnangle is counter-clockwise. If, however, edge23 has a delta-direction of 3, 2, or 6, then the tnangle is clockwise If edge23 has a delta-direction of 1 (I e., the same as edge 12), then comparing the slopes of the two edges breaks the tie (both are x-major) If edge 12 has a greater slope, then the tnangle is counter-clockwise. If edge23 has a delta-direction of 7 (the exact opposite of edge 12), then agam the slopes are compared, but with opposite results m terms of whether the triangle is clockwise or counter-clockwise. The same analysis can be exhaustively applied to all combinations of edge 12 and edge23 delta- directions, in every case determmmg the proper faced-ness. If the slopes are the same m the tie case, then the tnangle is degenerate (i.e., with no mtenor area). It can be explicitly tested for and culled, or, with proper numencal care, it could be let through as it will cause no pixels to render. One special case is when a tnangle splits the view plane, but that may be detected earlier m the pipeline (e.g , when front plane and back plane clipping are performed) Note m most cases only one side of a tnangle is rendered Thus, after the faced-ness of a tnangle is determined, if the face is the one to be rejected, then the triangle can be culled (i.e., subject to no further processmg with no pixels generated). Further note that this determination of faced-ness only uses one additional comparison (i.e., of the slope of edge 12 to that of edge23) beyond factors already computed. Many traditional approaches may utilize more complex computation (though at earlier stages of the set-up computation) Figure 13 is a flowchart of one embodiment of a method for filteπng samples stored m the super-sampled sample buffer to generate output pixels. First, a stream of bms are read from the super-sampled sample buffer (step 250) These may be stored in one or more caches to allow the sample-to-pixel calculation units 170 easy access durmg the convolution process (step 252). Next, the bms are exammed to determine which may contain samples that contnbute to the output pixel currently bemg generated by the filter process (step 254). Each sample that is m a bm that may contribute to the output pixel is then mdividually exammed to determine if the sample does indeed contnbute (steps 256-258). This determination may be based upon the distance from the sample to the center of the output pixel bemg generated. In one embodiment, the sample-to-pixel calculation units 170 may be configured to calculate this distance (i.e., the extent of the filter at sample's position) and then use it to mdex mto a table stonng filter weight values accordmg to filter extent (step 260). In another embodiment, however, the potentially expensive calculation for determining the distance from the center of the pixel to the sample (which typically mvolves a square root function) is avoided by usmg distance squared to mdex mto the table of filter weights. Alternatively, a function of x and y may be used in lieu of one dependent upon a distance calculation. In one embodiment, this may be accomplished by utilizing a floating point format for the distance (e g., four or five bits of mantissa and three bits of exponent), thereby allowing much of the accuracy to be mamtamed while compensatmg for the mcreased range m values. In one embodiment, the table may be implemented m ROM. However, RAM tables may also be used. Advantageously, RAM tables may, m some embodiments, allow the graphics system to vary the filter coefficients on a per-frame basis. For example, the filter coefficients may be vaned to compensate for known shortcomings of the display or for the user's personal preferences. The graphics system can also vary the filter coefficients on a screen area basis withm a frame, or on a per-output pixel basis Another alternative 20 embodiment may actually calculate the desired filter weights for each sample usmg specialized hardware (e.g., multipliers and adders). The filter weight for samples outside the limits of the convolution filter may simply be multiplied by a filter weight of zero (step 262), or they may be removed from the calculation entirely. Once the filter weight for a sample has been determined, the sample may then be multiplied by its filter weight (step 264) The weighted sample may then be summed with a running total to determine the final output pixel's color value (step 266). The filter weight may also be added to a running total pixel filter weight (step 268), which is used to normalize the filtered pixels Normalization advantageously prevents the filtered pixels (e.g., pixels with more samples than other pixels) from appearmg too bnght or too dark by compensatmg for gam introduced by the convolution process. After all the contnbuting samples have been weighted and summed, the total pixel filter weight may be used to divide out the gam caused by the filteπng (step 270) Finally, the normalized output pixel may be output for gamma correction, digital- to-analog conversion (if necessary), and eventual display (step 274). Figure 14 illustrates a simplified example of an output pixel convolution As the figure shows, four bms 288 A-D contam samples that may possibly contnbute to the output pixel. In this example, the center of the output pixel is located at the boundary of bms 288A-288D Each bm compnses sixteen samples, and an aπay of 2 four bms (2 x 2) is filtered to generate the output pixel Assuming circular filters are used, the distance of each sample from the pixel center determines which filter value will be applied to the sample. For example, sample 296 is relatively close to the pixel center, and thus falls withm the region of the filter havmg a filter value of 8 Similarly, samples 294 and 292 fall within the regions of the filter havmg filter values of 4 and 2, respectively. Sample 290, however, falls outside the maximum filter extent, and thus receives a filter value of 0 Thus sample 290 will not contnbute to the output pixel's value This type of filter ensures that the samples located the closest to the pixel center will contribute the most, while pixels located the far from the pixel center will contnbute less to the final output pixel values. This type of filtermg automatically performs anti-aliasing by smoothing any abrupt changes m the image (e.g., from a dark lme to a light background). Another particularly useful type of filter for anti-aliasing is a wmdowed smc filter. Advantageously, the wmdowed sine filter contams negative lobes that resharpen some of the blended or "fuzzed" image Negative lobes are areas where the filter causes the samples to subtract from the pixel bemg calculated. In contrast samples on either side of the negative lobe add to the pixel bemg calculated. Example values for samples 290-296 are illustrated m boxes 300-308. In this example, each sample compnses red, green, blue and alpha values, m addition to the sample's positional data. Block 310 illustrates the calculation of each pixel component value for the non-normalized output pixel. As block 310 mdicates, potentially undesirable gam is introduced mto the final pixel values (i.e., an out pixel havmg a red component value of 2000 is much higher than any of the sample's red component values). As previously noted, the filter values may be summed to obtain normalization value 308. Normalization value 308 is used to divide out the unwanted gam from the output pixel. Block 312 illustrates this process and the final normalized example pixel values. Note the values used herem were chosen for desenptive purposes only and are not meant to be limiting. For example, the filter may have a large number of regions each with a different filter value. In one embodiment, some regions may have negative filter values. The filter utilized may be a continuous function that is evaluated for each sample based on the sample's distance from the pixel center. Also note that floatmg pomt values may be 21 used for mcreased precision. A vanety of filters may be utilized, e g., cylinder, cone, gaussian, Katmull-Rom, wmdowed smc, Mitchell filter, box, tent. Full-Screen Anti-aliasing The vast majonty of current 3D graphics systems only provide real-time anti-aliasing for lmes and dots. While some systems also allow the edge of a polygon to be "fuzzed", this technique typically works best when all polygons have been pre-sorted m depth. This may defeat the purpose of having general-purpose 3D rendenng hardware for most applications (which do not depth pre-sort their polygons) In one embodiment, graphics system 112 may be configured to implement full-screen anti-aliasing by stochastically samplmg up to sixteen samples per output pixel, filtered by a 4x4-convolutιon filter Variable Resolution Super-Sampling Currently, the straight- forward brute force method of utilizing a fixed number of samples per pixel location, e.g., an 8x super-sampled sample buffer, would entail the use of eight times more memory, eight times the fill rate (i.e., memory bandwidth), and a convolution pipe capable of processing eight samples per pixel. Given the high resolution and refresh rates of current displays, a graphics system of this magnitude may be relatively expense to implement given today's level of integration In one embodiment, graphics system 112 may be configured to overcome these potential obstacles by implementing vanable resolution super-samplmg In this embodiment, graphics system 112 mimics the human eye's charactenstics by allocating a higher number of samples per pixel at one or more first locations on the screen (e.g., the pomt of foveation on the screen), with a drop-off m the number of samples per pixel for one or more second locations on the screen (e.g., areas farther away from the pomt of foveation) Dependmg upon the implementation, the pomt of foveation may be determined m a vanety of ways. In one embodiment, the pomt of foveation may be a predetermmed area around a certain object displayed upon the screen. For example, the area around a movmg cursor or the mam character m a computer game may be designated the pomt of foveation. In another embodiment, the pomt of foveation on the screen may be determined by head-tracking or eye-tracking. Even if eye/head/hand-tracking, cursor-based, or mam character-based pomts of foveation are not implemented, the pomt of foveation may be fixed at the center of the screen, where the majority of viewer's attention is focused the majonty of the time. Vaπable resolution super-samplmg is descnbed m greater detail below. Variable-Resolution Super-Sampled Sample buffer — Figures 15-19 A traditional frame buffer is one rectangular array of uniformly sampled pixels. For every pixel on the final display device (CRT or LCD), there is a smgle pixel or location of memory storage m the frame buffer (perhaps double buffered). There is a tnvial one-to-one correspondence between the 2D memory address of a given pixel and its 2D sample address for the mathematics of rendenng Stated another way, m a traditional frame buffer there is no separate notion of samples apart from the pixels themselves The output pixels are stored m a traditional frame buffer m a row/column manner correspondmg to how the pixels are provided to the display durmg display refresh. In a vanable-resolution super-sampled sample buffer, the number of computed samples per output pixel vanes on a regional basis. Thus, output pixels m regions of greater mterest are computed usmg a greater number 22 of samples, thus producmg greater resolution m this region, and output pixels in regions of lesser mterest are computed usmg a lesser number of samples, thus producmg lesser resolution m this region As previously noted, m some embodiments graphic system 112 may be configured with a vanable resolution super-sampled sample buffer. To implement vaπable resolution super-sampling, sample buffer 162 may be divided mto smaller pieces, called regions. The size, location, and other attnbutes of these regions may be configured to vary dynamically, as parameterized by run-tune registers on a per-frame basis. Turning now to Figure 15, a diagram of one possible scheme for dividing sample buffer 162 is shown. In this embodiment, sample buffer 162 is divided mto the following three nested regions: foveal region 354, medial region 352, and peπpheral region 350 Each of these regions has a rectangular shaped outer border, but the medial and the penpheral regions have a rectangular shaped hole m their center. Each region may be configured with certain constant (per frame) properties, e g., a constant density sample density and a constant size of pixel bm. In one embodiment, the total density range may be 256, i.e., a region could support between one sample every 16 screen pixels (4 x 4) and 16 samples for every 1 screen pixel. In other embodiments, the total density range may be limited to other values, e.g., 64. In one embodiment, the sample density vanes, sither linearly or non-lmearly, across a respective region. Note in other embodiments the display may be divided mto a plurality of constant sized regions (e.g , squares that are 4 x 4 pixels m size or 40 x 40 pixels m size). To simply perform calculations for polygons that encompass one or more region comers (e.g., a foveal region comer), the sample buffer may be further divided mto a plurality of subregions Tummg now to Figure 16, one embodiment of sample buffer 162 divided mto sub-regions is shown. Each of these sub-regions are rectangular, allowmg graphics system 112 to translate from a 2D address with a sub-region to a linear address m sample buffer 162. Thus, m some embodiments each sub-region has a memory base address, mdicatmg where storage for the pixels withm the sub-region starts. Each sub-region may also have a "stπde" parameter associated with its width Another potential division of the super-sampled sample buffer is circular. Tummg now to Figure 17, one such embodiment is illustrated For example, each region may have two radii associated with it (I e., 360-368), dividing the region mto three concentnc circular-regions. The circular-regions may all be centered at the same screen pomt, the fovea center pomt. Note however, that the fovea center-pomt need not always be located at the center of the foveal region. In some mstances it may even be located off-screen (i.e., to the side of the visual display surface of the display device). While the embodiment illustrated supports up to seven distinct circular- regions, it is possible for some of the circles to be shared across two different regions, thereby reducmg the distinct circular-regions to five or less. The circular regions may delmeate areas of constant sample density actually used. For example, in the example illustrated m the figure, foveal region 354 may allocate a sample buffer density of 8 samples per screen pixel, but outside the innermost circle 368, it may only use 4 samples per pixel, and outside the next circle 366 it may only use two samples per pixel. Thus, m this embodiment the rmgs need not necessarily save actual memory (the regions do that), but they may potentially save memory bandwidth mto and out of the sample buffer (as well as pixel convolution bandwidth). In addition to mdicatmg a different effective sample density, the rmgs may also 23 be used to mdicate a different sample position scheme to be employed As previously noted, these sample position schemes may stored m an on-chip RAM/ROM, or m programmable memory As previously discussed, m some embodiments super-sampled sample buffer 162 may be further divided mto bms For example, a bm may store a smgle sample or an aπay of samples (e g , 2x2 or 4x4 samples) In one embodiment, each bm may store between one and sixteen sample pomts, although other configurations are possible and contemplated Each region may be configured with a particular bm size, and a constant memory sample density as well Note that the lower density regions need not necessaπly have larger bm sizes In one embodiment, the regions (or at least the inner regions) are exact mteger multiples of the bm size enclosmg the region This may allow for more efficient utilization of the sample buffer m some embodiments Vaπable-resolution super-samplmg mvolves calculating a vaπable number of samples for each pixel displayed on the display device Certain areas of an image may benefit from a greater number of samples (e g , near object edges), while other areas may not need extra samples (e g , smooth areas havmg a constant color and bπghtness) To save memory and bandwidth, extra samples may be used only in areas that may benefit from the increased resolution For example, if part of the display is colored a constant color of blue (e g , as m a background), then extra samples may not be particularly useful because they will all simply have the constant value (equal to the background color bemg displayed) In contrast, if a second area on the screen is displaying a 3D rendered object with complex textures and edges, the use of additional samples may be useful m avoidmg certain artifacts such as aliasing A number of different methods may be used to determine or predict which areas of an image would benefit from higher sample densities For example, an edge analysis could be performed on the final image, and with that mformation bemg used to predict how the sample densities should be distnbuted The software application may also be able to mdicate which areas of a frame should be allocated higher sample densities A number of different methods may be used to implement vanable-resolution super samplmg These methods tend to fall mto the following two general categones (1) those methods that concern the draw or rendenng process, and (2) those methods that concern the convolution process For example, samples may be rendered mto the super-samplmg sample buffer 162 usmg any of the following methods 1) a uniform sample density, 2) varymg sample density on a per-region basis (e g , medial, foveal, and penpheral), and 3) varymg sample density by changmg density on a scan-lme basis (or on a small number of scan lmes basis) Varymg sample density on a scan-line basis may be accomplished by usmg a look-up table of densities For example, the table may specify that the first five pixels of a particular scan lme have uiree samples each, while the next four pixels have two samples each, and so on On the convolution side, the following methods are possible 1 ) a uniform convolution filter, 2) continuously variable convolution filter, and 3) a convolution filter operating at multiple spatial frequencies A uniform convolve filter may, for example, have a constant extent (or number of samples selected) for each pixel calculated In contrast, a continuously vanable convolution filter may gradually change the number of 24 samples used to calculate a pixel The function may be vary continuously from a maximum at the center of attention to a minimum m peπpheral areas Different combmations of these methods (both on die rendenng side and convolution side) are also possible For example, a constant sample density may be used on the rendenng side, while a continuously vanable convolution filter may be used on the samples Different methods for determmmg which areas of the image will be allocated more samples per pixel are also contemplated In one embodiment, if the image on the screen has a mam focal pomt (e g , a character like Mano m a computer game), then more samples may be calculated for the area around Mano and fewer samples may be calculated for pixels m other areas (e g , around the background or near the edges of the screen) In another embodiment, the viewer's pomt of foveation may be determined by eye/head/hand-tracking In head-tracking embodiments, the direction of the viewer's gaze is determined or estimated from the onentation of the viewer's head, which may be measured usmg a vanety of mechanisms For example, a helmet or visor worn by the viewer (with eye/head trackmg) may be used alone or m combmation with a hand-tracking mechanism, wand, or eye-tracking sensor to provide onentation mformation to graphics system 112 Other alternatives mclude head-tracking usmg an mfrared reflective dot placed on the user's forehead, or usmg a pair of glasses with head- and or eye-tracking sensors built m One method for usmg head- and hand-tracking is disclosed in U S Patent No 5,446,834 (entitled "Method and Apparatus for High Resolution Virtual Reality Systems Usmg Head Tracked Display," by Michael Deenng, issued August 29, 1995), which is incorporated herem by reference m its entirety Other methods for head trackmg are also possible and contemplated (e g , infrared sensors, electromagnetic sensors, capacitive sensors, video cameras, sonic and ultrasonic detectors, clothing based sensors, video trackmg devices, conductive ink, strain gauges, force-feedback detectors, fiber optic sensors, pneumatic sensors, magnetic trackmg devices, and mechanical switches) As previously noted, eye-tracking may be particularly advantageous when used m conjunction with head-tracking In eye-tracked embodiments, the direction of the viewer's gaze is measured directly by detecting the onentation of the viewer's eyes m relation to the viewer's head This mformation, when combmed with other mformation regarding the position and onentation of the viewer's head m relation to the display device, may allow an accurate measurement of viewer's pomt of foveation (or pomts of foveation if two eye-tracking sensors are used) One possible method for eye trackmg is disclosed m U S Patent No 5,638,176 (entitled "Inexpensive Interferometπc Eye Trackmg System") Other methods for eye trackmg are also possible and contemplated (e.g , the methods for head trackmg listed above) Regardless of which method is used, as the viewer's pomt of foveation changes position, so does the distnbution of samples For example, if the viewer's gaze is focused on the upper left-hand comer of the screen, the pixels correspondmg to the upper left-hand comer of the screen may each be allocated eight or sixteen samples, while the pixels m the opposite comer (I e , the lower right-hand comer of the screen) may be allocated only one or two samples per pixel Once the viewer's gaze changes, so does the allotment of samples per pixel When the viewer's gaze moves to the lower right-hand comer of the screen, the pixels m the upper left-hand comer of the screen may be allocated only one or two samples per pixel Thus the number of samples per pixel may be actively changed for different regions of the screen m relation the viewer's pomt of foveation Note m some embodiments, multiple users may be each have head/eye/hand trackmg mechanisms that provide mput to graphics system 112 In these embodiments, there may conceivably be two or more pomts of foveation on the 25 screen, with correspondmg areas of high and low sample densities. As previously noted, these sample densities may affect the render process only, the filter process only, or both processes. Tummg now to Figures 18A-B, one embodiment of a method for apportioning the number of samples per pixel is shown. The method apportions the number of samples based on the location of the pixel relative to one or more pomts of foveation. In Figure 18A, an eye- or head-tracking device 360 is used to determine the pomt of foveation 362 (I e., the focal pomt of a vιewer " s gaze). This may be determined by usmg trackmg device 360 to determine the direction that the viewer's eyes (represented as 364 in the figure) are facmg As the figure illustrates, m this embodiment, the pixels are divided mto foveal region 354 (which may be centered around the pomt of foveation 362), medial region 352, and penpheral region 350. Three sample pixels are mdicated m the figure. Sample pixel 374 is located withm foveal region 314. Assummg foveal region 314 is configured with bms havmg eight samples, and assummg the convolution radius for each pixel touches four bms, then a maximum of 32 samples may contnbute to each pixel. Sample pixel 372 is located withm medial region 352. Assummg medial region 352 is configured with bms havmg four samples, and assummg the convolution radius for each pixel touches four bms, then a maximum of 16 samples may contnbute to each pixel. Sample pixel 370 is located withm peπpheral region 350 Assummg peπpheral region 370 is configured with bms havmg one sample each, and assummg the convolution radius for each pixel touches one bm, then there is a one sample to pixel coπelation for pixels in peπpheral region 350 Note these values are merely examples and a different number of regions, samples per bm, and convolution radius may be used. Tummg now to Figure 18B, the same example is shown, but with a different pomt of foveation 362. As the figure illustrates, when trackmg device 360 detects a change m the position of pomt of foveation 362, it provides mput to the graphics system, which then adjusts the position of foveal region 354 and medial region 352. In some embodiments, parts of some of the regions (e g., medial region 352) may extend beyond the edge of display device 84. In this example, pixel 370 is now withm foveal region 354, while pixels 372 and 374 are now withm the peπpheral region. Assummg the sample configuration as the example m Figure 18 A, a maximum of 32 samples may contnbute to pixel 370, while only one sample will contnbute to pixels 372 and 374 Advantageously, this configuration may allocate more samples for regions that are near the point of foveation (i.e., the focal pomt of the viewer's gaze) This may provide a more realistic image to the viewer without the need to calculate a large number of samples for every pixel on display device 84. Tummg now to Figures 19A-B, another embodiment of a computer system configured with a vanable resolution super-sampled sample buffer is shown In this embodiment, the center of the viewer's attention is determined by position of a mam character 362. Medial and foveal regions are centered around mam character 362 as it moves around the screen. In some embodiments mam character may be a simple cursor (e.g., as moved by keyboard mput or by a mouse). In still another embodiment, regions with higher sample density may be centered around the middle of display device 84 's screen. Advantageously, this may require less control software and hardware while still providmg a shaper image m the center of the screen (where the viewer's attention may be focused the majonty of the time). 26 Computer Network — Figure 20 Referring now to Figure 20, a computer network 500 is shown compnsmg at least one server computer 502 and one or more client computers 506A-N. (In the embodiment shown m Figure 4, client computers 506A-B are depicted). One or more of the client systems may be configured similarly to computer system 80, with each havmg one or more graphics systems 112 as descnbed above Server 502 and chent(s) 506 may be jomed through a vanety of connections 504, such as a local-area network (LAN), a wide-area network (WAN), or an Intemet connection. In one embodiment, server 502 may store and transmit 3-D geometry data (which may be compressed) to one or more of clients 506. The clients 506 receive the compressed 3-D geometry data, decompress it (if necessary) and then render the geometry data. The rendered image is then displayed on the client's display device. The clients render the geometry data and display the image usmg super-sampled sample buffer and real-time filter techniques described above In another embodiment, the compressed 3-D geometry data may be transfened between client computers 506 Additional Graphics System Features Dependmg upon the implementation, computer system 80 may be configured to perform one or more of the following techniques m real-tune usmg graphics system 112 (and super-sampled sample buffer 162): high- quality texture filtermg, bump mappmg, displacement mappmg, multiple texture mappmg, decompression of compressed graphics data, per-pixel Phong shadmg, depth of field effects, alpha buffering, soft-key output, 12-bit effective lmear output, and mtegral eye-head-hand trackmg. Each of these techniques will be descnbed detail further below A. Texture Filterm - Figures 21-22 One popular technique to improve the realism of images displayed on a computer system is texture mappmg. Texture mappmg maps an image compnsmg a plurality of pixel values or texel values (called a "texture map") onto the surface of an object. A texture map is an image which can be wrapped (or mapped) onto a three- dimensional (3D) object. An example of a texture map 20 is illustrated in Figure 21 A Texture map 20 is defined as a collection of texture elements 22a-n ("texels"), with coordmates U and V (similar to X and Y coordmates on the display or "screen space") In Figure 2 IB, an example of texture mappmg is shown. As the figure illustrates, texture map 20 is mapped onto two sides of a three dimensional cube Figure 21C shows another example of texture mappmg, but this time onto a spherical object. Another example would be to map an image of a pamtmg with mtncate details onto a senes of polygons representing a vase. While texture mappmg may result m more realistic scenes, awkward side effects of texture mappmg may occur unless the graphics subsystem can apply texture maps with correct perspective. Perspective-corrected texture mappmg mvolves an algonthm that translates texels (l e., pixels from the bitmap texture image) mto display pixels m accordance with the spatial onentation of the surface In conjunction with texture mappmg, many graphics subsystems utilize bilinear filtermg, anti-aliasing, and mip mappmg to further improve the appearance of rendered images Bilinear filteπng improves the appearance of texture mapped surfaces by considering the values of a number of adjacent texels (e.g , four) m order to detemune the value of the displayed pixel. Bilinear filtermg may reduce some of the "blockiness" that results from simple pomt samplmg when adjacent display pixel values are defined by a smgle texel. 27 As previously descnbed, aliasing refers to the jagged edges that result from displaying a smooth object on a computer display. Aliasing may be particularly disconcerting at the edges of texture maps. Anti-aliasing (i.e., minimizing the appearance of jagged edges) avoids this distraction by reducing the contrast between the edges where different sections of the texture map meet. This is typically accomplished by adjusting pixel values at or near the edge. Mip-mappmg mvolves stonng multiple copies of texture maps, each digitized at a different resolution. When a texture-mapped polygon is smaller than the texture image itself, undesirable effects may result durmg texture mappmg. Mip mappmg avoids this problem by providing a large version of a texture map for use when the object is close to the viewer (i.e., large), and smaller versions of the texture map for use when the object shrinks from view. A imp-map may be visualized as a pyramid of filtered versions of the same texture map. Each map has one-half the lmear resolution of its precedmg map, and has therefore one quarter the number of texels. The memory cost of this organization, where the coarsest level has only one texel, is 4/3 (I e., 1 + 'A + '/16 + . . .) the cost of the ongmal map. The acronym "mip" stands for "multum m parvo" a Latm phrase meaning " many things in a small place" TI e imp-map scheme thus provides pre-filtered textures, one of which is selected at run time for use m rendermg In general, the desired level will not exactly match one of the predetermmed levels m the imp-map Thus, interpolation may be mvolved to calculate the desired level. Bilinear interpolation may be used if the texel to be looked up is not exactly on the mteger boundanes of the predetermmed mip-map levels. Similar two-dimensional lmear interpolations are computed m each mip-map when scaled (u, v) values for texture table lookup are not mteger values To assure contmuity when rapidly changmg images (e g., during animation), the effects of the four texels which enclose the scaled (u, v) values are considered, based upon their lmear distances from the reference pomt m texel space. For example, if the scaled (u, v) values are (3.7, 6 8), the weighted average of texels (3, 6), (4, 6), (3, 7), and (4, 7) is taken Turning now to Figure 22, a set of mip maps is shown. As the figure illustrates, each mip map is a two dimensional image, where each successive mip map is one half the size of the previous one. For example, if level 0 (I e., texture map 20) is sixteen by sixteen texels, then level 1 (mip map 22) is eight by eight texels, level 2 (imp map 24) is four by four texels, level 3 ( ip map 24) is two by two texels, and level 4 (mip map 28) is a smgle texel. Each subsequent imp map is one half the dimension of the previous imp map Thus, each subsequent mip map has one quarter the area, number of texels, and resolution of the previous mip map Note however, that other ratios are also possible and that imp maps need not be square. Tn-lmear filtermg may be used to smooth out edges of mip mapped polygons and prevent movmg objects from displaying a distracting 'sparkle' resultmg from mismatched texture mtersections. Tnlmear filtermg mvolves blendmg texels from two neighboring mip maps (e.g., blendmg texels from mip map 20 and mip map 22). The texel addresses m the neighboring mip maps are related by their addresses. For example, a particular texel at address (UN) m level Ν corresponds to the texel at address (U/2, V/2) m level Ν+l . This is represented by texels 30 and 32 m the figure (each marked with an "x") Current texture mappmg hardware tends to implement simple bi- or tπ-lmear interpolation of mip-map textured images Bi-linear filters, however, are effectively "tent" filters that are uniform m texture space, not screen space Uniformity in screen space, however, tends to result m a more realistic image. 28 Currently, most high quality texture mappmg is actually performed by software. While a vanety of different techniques are used, most may be classified generally as "elliptical filters" (i.e., elliptical m texture space, but circular m screen space). These elliptical filters produce more realistic results, but are also considerably more complex than a tent filter. This complexity has prevented most real-time hardware implementations. In one embodiment, graphics system 112 may be configured to perform real-time high quality texture mappmg by convertmg texels mto micro-polygons (e.g., tπangles) at render time. These micro-polygons are then rendered mto super-sampled sample buffer 162 usmg bi- lmear interpolation. The final filtermg (which produces the high quality image) is deferred until the convolution is performed. This allows all samples that might effect the final pixel value to be wntten mto sample buffer 162 before the pixel value is calculated. The final filteπng may then advantageously be performed m screen space. In one embodiment, one to two hundred samples may be filtered to generate a smgle pixel. This may significantly improve the appearance of the final image m some embodiments when compared with traditional hardware texture mappmg systems that only filter four to eight texels to create a pixel. In one embodiment, graphics system 112 may also be configured to perform one or mort of the following advanced texturing techniques: bump mappmg, displacement mappmg, and multiple texture mappmg. B. Bump Mappmg Bump mappmg perturbs the normal on a surface to create what appears to be small wrinkles or bumps on the surface This technique breaks down near the silhouette of an object (because the silhouette of the object is m fact unchanged, the bumps implied by the shadmg are not visible m the geometry), and at near-glancmg angles to the surface (because there is no blocking or geometric attenuation due to the bumps. In general, though, as long as the bumps are very small and the object is some distance away, bump mappmg is an effective way to imply small deformations to a shape without actually changmg the geometry. C Displacement Mappmg Displacement mappmg actually moves the surface by a given amount m a given direction Rendenng displacement-mapped surfaces can present a challenge to some systems, particularly when the displacements become large. The results are often much better than with bump mappmg, because displacement mapped objects may actually exhibit self-hiding and potentially shelf-shadowmg features, as well as a changed silhouette. P. Multiple Texture Mappmg Multiple texture mappmg mvolves blendmg a number of different texture maps together to from the texture applied to the object. For example, a texture of fabric may be blended with a texture of marble so that it may appear that the fabnc is semi-transparent and covering a marble object Another example of multiple texture mappmg is taking a texture map of coπesponding light and dark areas (i.e., a low-frequency shadow map), and then blendmg the shadow map with a texture (e.g., a high- frequency texture map). Multiple texture mappmg may also be used for "micro-detail" applications. For example, when a viewer zooms m on a texture-mapped wall, the texture map for the wall may be blended with a low-resolution mtensity map to provide more realistic imperfections and vaπations m the finish of the wall. 29 E. Decompression of Compressed Graphics Data As previously noted, some embodiments of graphics system 112 may be configured to receive and decompress compressed 3D geometry data. This may advantageously reduce the memory bandwidth requirements withm graphics system 112, as well as allow objects with a larger number of polygons to be rendered m real time. F. Per-pixel Phong Shadmg As previously noted, m some embodiments graphics system 112 may be configured to break textures mto sub-pixel tnangle fragments (see Texture Filtermg above). By combmmg this feature with geometry compression (see Decompression of Compressed Graphics Data above) and an extremely high triangle render rate, graphics system 112 may, in some embodiments, be capable of achievmg image quality nvalmg, equalmg, or even surpassing that of per-pixel Phong shading These high quality images may be achieved by finely tessellating the objects to be rendered usmg micro-polygons By finely tesselating the objects, a smoother and more accurate image is created without the need for per-pixel Phong shadmg For example, hardware m graphics system may be configured to automatically turn all primitives mto micro-tnangles (I e , triangles that are one pixel or less m size) before lighting and texturing is performed. G. Soft-key Output In some environments, users of graphics systems may desire the ability to output high quality anh-aliased rendered images that can be overlaid on top of a live video stream. While some systems exist that offer this capability, they are typically quite expensive. In one embodiment, graphics system 112 may be configured to inexpensively generate high quality overlays. In one embodiment, graphics system 112 may be configured to generate an accurate soft edge alpha key for video output and down stream alpha key g. The alpha key may be generated by sample-to-pixel calculation units 170, which may perform a filtermg function on the alpha values stored m sample buffer 162 to form "alpha pixels." Each alpha pixel may correspond to a particular output pixel In one embodiment, the alpha pixels may be output usmg DAC 178 A while the color output pixels may be output by DAC 178B. In another embodiment, this soft edge alpha key overlay is then output m a digital format to an external mixing unit which blends the overlay with a live video feed. The alpha pixels correspondmg to each output pixel will detemune how much of the live video shows through the correspondmg pixel of the overlay. In one embodiment, for example, the greater the alpha pixel value, the more opaque the pixel becomes (and the less the live video feed shows through the pixel). Similarly, the smaller the alpha pixel value, the more transparent the pixel becomes. Other embodiments are also possible and contemplated. For example, the live video feed could be mput mto computer system 80 or graphics system 112. Graphics system 112 could then blend the two sources internally and output the combmed video signal. H. 12-bit Effective Lmear Output While 12-bit (lmear light) color depth (I e., 12-bιts of data for each of red, green, and blue) is considered ideal m many embodiments, possible limitations m sample memones 162 may limit the storage space per sample to a lesser value (e.g., 10-bιts per color component). In one embodiment, graphics system 112 may be configured to dither samples from 12-bιts to 10-bιts before they are stored in sample buffer 162. Durmg the final anti- 30 aliasing computation m sample-to-pixel calculation units 170A-D, the additional bits may effectively be recovered. After normalization, the resulting pixels may be accurate to 12-bιts (lmear light). The output pixels may be converted to nonlmear light, and after the translation, the results may be accurate to 10 bits (non-linear light). After conversion from lmear to non-lmear light, the resulting pixels may thus be accurate to 10-bιts. I. Integrated Eye-Head-Hand Trackmg As previously noted, some embodiments of graphics system 112 may be configured to support eye, head, and or hand trackmg by modifymg the number of samples per pixel at the viewer's pomt of foveation. J. Alpha Blendmg, Foggmg, and Depth-Cueing Alpha blendmg is a technique that controls the transparency of an object, allowmg realistic rendenng of translucent surfaces such as glass or water. Additional atmospheπc effects that are found m rendenng engmes mclude foggmg and depth cuemg Both of these techniques obscure an object as it moves away from the viewer. Blur is also somewhat related and may be implemented by performmg low-pass filtermg durmg the filtermg and sample-to-pixel calculation process (e g , by usmg a larger extent durmg the filtermg process) by sample-to-pixel calculation units 170A-D An alpha value may be generated that can be used to blend the cunent sample mto the sample buffer Although the embodiments above have been described m considerable detail, other versions are possible. Numerous vanations and modifications will become apparent to those skilled m the art once the above disclosure is fully appreciated. It is mtended that the followmg claims be mterpreted to embrace all such vanations and modifications. Note the headmgs used herem are for organizational purposes only and are not meant to limit the descπption provided herem or the claims attached hereto. 31

Claims: What is claimed is: 1. A graphics system compnsmg: a graphics processor configured receive 3D graphics data, wherem the graphics processor is configured to generate a plurality of samples from the 3D graphics data; a super-sampled sample buffer coupled to receive and store the samples from the graphics processor; and a sample-to-pixel calculation unit coupled to receive samples from the super-sampled sample buffer, wherem the sample-to-pixel calculation unit is configured to form output pixels from said stored samples and convey the output pixels to a display device without stonng the output pixels m an intervening frame buffer. 2. The graphics system as recited m claim 1, wherem said super-sampled sample buffer is configured to double buffer at least a portion of each stored sample. 3. The graphics system as recited m claim 1, wherem said sample-to-pixel calculation unit is configured to form the output pixels m real time. 4. The graphics system as recited m any of claims 1-3, wherem the sample-to-pixel calculation unit is configured to form each output pixel from the samples once per display device refresh cycle. 5. The graphics system as recited m any of claims 1-3, wherem the sample buffer is further configured to store alpha mformation for at least a portion of the samples stored therein. 6. The graphics system as recited m any of claims 1-3, wherem the sample-to-pixel calculation unit is programmable to change parameters governing the filtermg performed by the convolution unit. 7. The graphics system as recited m any of claims 1-3, wherem the sample-to-pixel calculation unit is programmable to change parameters govemmg the filtermg performed by the convolution unit on a frame-by- frame basis. 8. The graphics system as recited m any of claims 1-3, further compnsmg a second sample-to-pixel calculation unit, wherem the second sample-to-pixel calculation umt and the first sample-to-pixel calculation unit are configured to operate m parallel. 9. The graphics system as recited m any of claims 1-3, wherem each sample-to-pixel calculation unit is configured to receive samples correspondmg to a particular region of the sample buffer. 10. The graphics system as recited in claim 9, wherem the particular regions overlap. 32 11. The graphics system as recited m any of claims 1-3, wherem the samples are stored m the sample buffer m bms. 12. The graphics system as recited m claim 11, wherem each bm defines the approximate position of each sample withm the bm, wherem the precise position of each sample withm the bm is determined by add g x-offsets and y-offsets associated with the sample to the sample's bm position. 13. The graphics system as recited m any of claims 1-3, wherem each sample's x-offset and y-offset are stored m the sample buffer. 14. The graphics system as recited m any of claims 1-3, further compnsmg a sample position memory coupled to the sample-to-pixel calculation unit, wherem each sample's x-offset and y-offset are stored in the sample position memory 15 The graphics system as recited m any of claims 1-3, wherem the sample-to-pixel calculation unit is configured to determine a particular output pixel's color values by- multiplying each sample that falls withm a predetermmed region around the particular output pixel's center by a weighting factor; and summing the weighted samples. 16. A method for operatmg a graphics system compnsmg: receivmg 3D graphics data, wherem the 3D graphics data compnses a plurality of graphics primitives, calculating a plurality of sample positions, determmmg which sample positions are withm the graphics primitives, rendenng the samples that are withm the graphics primitives, stonng the rendered samples m sample buffer, wherem at least a portion of each stored sample is double-buffered; and filtermg the stored samples once per screen refresh cycle to generate an output pixel. 17. The method as recited m claim 16, wherem the filtermg compnses: reading a group of samples from the sample buffer; 33 determmmg which samples withm the group are located withm a predetermmed extent from the center of the output pixel bemg generated, applymg a scalmg factor to each sample withm the predetermmed distance, summing the scaled samples to form the output pixel; and normalizing the output pixel 18. The method as recited in claim 16, wherem the filteπng compnses readmg a group of samples from the sample buffer, determmmg which samples withm the group are located withm a predetermmed distance from the center of the output pixel bemg generated, applymg a scalmg factor to each sample withm the predetermmed distance, summing the scaled samples to form the output pixel; and normalizing the output pixel 19. The method as recited m claim 17, wherem the scalmg factor varies as a function of the sample's distance from the center of the output pixel or the sample's x-offset and y-offset from the center of the output pixel 20. The method as recited in any of claims 16-19, further compnsmg stonng an alpha value for at least a portion of the samples stored in the sample buffer 21. The method as recited m any of clauns 16-19, wherem the filtermg compnses mathematically manipulating samples located withm a predetermmed distance from the center of the output pixel or withm a predetermmed filter extent. 22. The method as recited m any of claims 16-19, wherem the filter is changeable at least as frequently as the screen refresh cycle 23. The method as recited m any of clauns 16-19, wherem the stonng comprises stonng the samples in bms, where each sample's position is determined by addmg an x-offset and a y-offset to the bm's position 34 24. The method as recited m claim 23, wherem the filtermg compnses readmg at least part of one or more columns of bms from the sample buffer, wherem the columns overlap, wherem more than one of said columns are filtered m parallel. 25. The method as recited m any of claims 16-19 and 24, further compnsmg stonng x-offsets and y-offsets for each sample stored m the sample buffer. 26. The method as recited m any of clauns 16-19 and 24, wherem the number of samples contnbutmg to each output pixel vanes. 27. A computer system configured to display 3D graphics images, the system compnsmg a microprocessor; a mam memory, a bus couplmg the microprocessor and the mam memory; and a graphics system accordmg any of clauns 1-15 28. A computer software program embodied on a earner medium, wherem the software program compnses a plurality of mstmctions configured to direct a graphics processor to perform the method of any of clauns 16- 26 29. A graphics system comprising- a graphics processor configured to calculate a plurality of samples, wherem said graphics processor is programmable to vary the positions of said samples, a sample buffer coupled to said graphics processor and configured to receive and store said plurality of samples, wherem said samples are double-buffered m said sample buffer; and a sample-to-pixel calculation unit coupled to read and filter said samples from said sample buffer to form output pixels. 30. The graphics system as recited in claim 29, wherem said sample- to-pixel calculation unit filters said samples m real time and duectly delivers said output pixels to a display device without an intervening frame buffer. 35 31. The graphics system as recited m claims 29 or 30, wherem said graphics processor is configured to vary the positions of said samples on one of the followmg: a per-frame basis, a per-pixel basis, a per-scan lme basis, a per region basis, a group of pixels basis, and a group of scan lmes basis 32. The graphics system as recited in clauns 29 or 30, wherein said graphics processor is configured to vary the density of said plurality of samples on a per-frame basis, a per-pixel basis, a per-scan lme basis, a per region basis, a group of pixels basis, or a group of scan lmes basis 33. The graphics system as recited m claims 29 or 30, further compnsmg a sample position memory coupled to said graphics processor, wherem said sample position memory is configured to store sample position mformation accordmg to one or more sample position schemes, wherem said graphics processor is configured to read said sample position mformation from said sample position memory 34. The graphics system as recited in clauns 29 or 30, further compnsmg a sample position memory coupled to said graphics processor, wherem said sample position memory is configured to store sample position mformation accordmg to one or more sample position schemes and one or more sample densities, wherem said graphics processor is configured to read said sample position mformation correspondmg to a selected sample position scheme and a selected sample position density from said sample position memory 35. The graphics system as recited m claims 29 or 30, further compnsmg a programmable sample position memory coupled to said graphics processor, wherem graphics processor is configured to read sample position mformation from said sample position memory. 36. The graphics system as recited in claim 35, wherem said sample position memory is configured to store said sample position mformation as x-offsets and y-offsets. 37. The graphics system as recited in claim 36, wherem said graphics processor is configured to generate said samples accordmg to sample positions calculated by combmmg said x- and y-offsets with one of the following predetermined bm coordmates or predetermmed pixel center coordmates. 38. The graphics system as recited m claim 35, wherem said sample- to-pixel calculation unit is configured to filter samples read from said sample buffer once per pixel per frame accordmg to sample position mformation stored m said sample position memory 39. The graphics system as recited m claims 29 or 30, wherem said graphics processor is programmable to select one of the followmg algoπthms with which to generate said sample positions: regular gnd spacmg, stochastic spacmg, or perturbed regular gnd spacmg. 40 The graphics system as recited m claims 29 or 30, wherem said sample buffer is super-sampled. 36 41. The graphics system as recited m claims 29 or 30, further compnsmg a sample position calculation unit compnsmg hardware selected from the group consisting of: a random number generator, a pseudo-random function generator, a table of random numbers, and a table of random number seeds. 42. A method for rendenng images usmg a graphics system, the method compnsmg: receivmg a set of 3D graphics data, wherem said 3D graphics data comprises at least one graphics primitive; generating a plurality of sample positions ; selectmg the sample positions that are withm said at least one primitive, calculatmg samples correspondmg to the selected samples positions; stonng the calculated samples mto a sample buffer; and filtermg the stored samples to generate output pixels, wherem the filtermg is performed once per output pixel per frame. 43. The method as recited m claim 42, wherem said generatmg further compnses selectmg one of a plurality of sample position generating algonthms. 44. The method as recited m claim 43, wherein said generating further comprises selectmg one of the followmg algonthms: stochastic, regular gnd, perturbed regular grid. 45. The method as recited m claim 42, wherem said generatmg comprises calculatmg random offsets to be added to regular grid positions. 46. The method as recited m claim 42, wherem said generatmg compnses: readmg random offsets from a table of random offsets; and addmg the offsets to regular gnd positions. 47. The method as recited m claim 46, wherem said random offsets compnse x-offsets and y-offsets, and wherem said x-offsets and said y-offsets are limited to predetermmed minimum and maximum values 48. The method as recited m claim 42, further compnsmg stonng said generated sample positions m a double- buffered sample position memory 37 49 The method as recited m claim 42, wherem each sample has a correspondmg sample position, wherem the samples are organized mto bms, wherem each bm has a particular screen position, wherem each sample position is an x-offset and y-offset from the correspondmg bm's x and y screen position 50. The method as recited m claim 42, wherein said generatmg compnses evaluating a formula usmg a stored counter value as input. 51. The method as recited m claims 42 or 48, wherem said sample buffer is super-sampled 52. The method as recited m claim 42, wherem a first portion of each sample's mformation is double-buffered, and wherem a second portion of each sample's mformation is smgle buffered. 53. A computer system compnsmg: a microprocessor, a mam memory coupled to said microprocessor; and a graphics system as recited m any of claims 29-41. 54. A graphics device driver embodied on a earner media, wherem said graphics device dnver compnses a plurality of mstmctions, wherem said plurality of mstmctions are configured to perform the method of any of claims 42-52. 55. The graphics device dnver as recited m claim 54, wherem said earner medium is a computer-readable medium or a transmission medium 56. A graphics system compnsmg a graphics processor configured to receive 3D graphics data, wherem said 3D graphics data compnses a plurality graphics primitives, wherem said graphics processor is configured to generate a plurality of samples from said 3D graphics data, wherem said samples compπse color and alpha mformation; a super-sampled sample buffer coupled to receive and store said samples from said graphics processor, wherem said sample buffer is configured to double-buffer at least a portion of each stored sample; and a sample-to-pixel calculation unit coupled to receive and filter samples from said super-sampled sample buffer to form output pixels and alpha pixels m real tune, wherem said alpha pixels are usable to form an alpha key 38 57. The computer system as recited m claim 56, wherem said graphics system is further configured to receive a video mput signal and blend said video mput signal with said output pixels accordmg to said alpha pixels. 58. The computer system as recited m claims 56 or 57, wherem said sample-to-pixel calculation unit is configured to convey said output pixels to said display device without stonng said output pixels m a traditional frame buffer 59. The graphics system as recited m claims 56 or 57, wherem said output pixels and said alpha pixels key are generated once for each pixel m each frame of said 3D graphics data 60 A method for operating a graphics system compnsmg receivmg 3D graphics data, wherem said 3D graphics data compnses a plurality of graphics primitives, calculating a plurality of sample positions, determmmg which sample positions are withm said graphics primitives, rendermg the samples that are withm the graphics primitives, stonng the rendered samples m sample buffer, stonng an alpha value for at least a portion of the samples stored m the sample buffer; and filtermg the stored samples once per screen refresh cycle to generate an output pixel and an alpha pixel, wherem said alpha pixels are usable to form an alpha key. 61. The method as recited in claim 60, further compnsmg receivmg a video mput signal, and blendmg said video mput signal with said output pixels accordmg to said alpha pixels 62. The method as recited in claim 60, wherem said filtermg further compnses readmg a group of samples from the sample buffer, determmmg which samples withm the group are located withm a predetermmed distance from the center of the output pixel bemg generated, 39 applymg a scalmg factor to each sample withm the predetermmed distance; and summing the scaled samples to form the output pixel 63 The method as recited in claim 60, wherem said scalmg factor vanes accordmg to the sample's distance from a predetermmed position on the output pixel 64. The method as recited m claim 60, wherem said scalmg factor varies accordmg to the sample's x-offset and y-offset from a predetermmed position on the output pixel 65. The method as recited m claim 60, wherem said filtermg is changeable at least as frequently as the screen refresh cycle 66 The method as recited m claim 60, wherem said storing compnses stonng the samples m bms, where each sample's position is determined by adding an x-offset and a y-offset to the bm's position 67 The method as recited m claim 60, further compnsmg stormg x-offsets and y-offsets for each sample stored in the sample buffer. 68. The method as recited in claim 60, wherem the filter is changeable at least as frequently as the screen refresh cycle. 69. The method as recited m claim 60, wherem the number of samples contnbuting to each output pixel vanes. 70 A computer system configured to display 3D graphics images, said system compnsmg a microprocessor, a mam memory, a bus couplmg said microprocessor and said mam memory, and a graphics system coupled to said mam memory, wherem said graphics system compnses: a graphics processor configured receive 3D graphics data, wherem said 3D graphics data compnses one or more graphics primitives, wherem said graphics processor is configured to generate a plurality of samples, each compnsmg color and alpha values, a sample buffer coupled to receive and store said samples from said graphics processor, wherem said sample buffer is configured to double-buffer at least a portion of each stored sample, and 40 a sample-to-pixel calculation unit coupled to receive samples from said sample buffer, wherem said sample-to-pixel calculation unit is configured to form output pixels and alpha pixels m realtime, wherem said alpha pixels are usable to form an alpha key 71. The computer system as recited m claim 70, wherem said alpha key is a soft edge alpha key. 72. The computer system as recited m claim 70, wherem said computer system is further configured to receive a video mput signal and blend said video input signal with said output pixels accordmg to said alpha pixels. 73. A computer software program embodied on computer readable media, wherem said software program compnses a plurality of mstmctions configured to direct a graphics processor to generate a plurality of sample positions, calculate samples for at least a subset of said sample positions, wherem said sample compnse both color mformation and alpha mformation, store said samples m a sample buffer, wherem at least of portion of each stored sample is double-buffered; read one or more of said samples from the sample buffer; filter said one or more samples once per screen refresh cycle to form output pixels with alpha mformation; and convey the output pixels to a display device 74 The computer software program as recited m claim 73, wherem said plurality of mstmctions are configured to filter said alpha mformation from said samples separately from said color mformation 75. The computer software program as recited m claim 73, wherem said plurality of instructions are configured to filter said alpha mformation usmg a different filter than the filter used for the color mformation. 76. The computer software program as recited m claim 73, wherem said plurality of mstmctions are further configured to duect a graphics processor to overlay the output pixels on a video background accordmg to said alpha key mformation. 77. The computer software program as recited m claim 73, wherem said plurality of mstmctions are further configured to modify the filter used durmg the convolution 78. The computer software program as recited m claim 73, wherem more than one sample contπbutes to each output pixel 41 79 The computer software program as recited m claim 73, wherem said output pixels are conveyed to a display device without bemg stored m a frame buffer 80. A graphics system compnsmg: a graphics processor configured to generate a plurality of samples; a sample buffer coupled to said graphics processor for stonng said samples; and a sample-to-pixel calculation unit coupled to said sample buffer, wherem said sample-to-pixel calculation unit is configured to select and filter stored samples to form output pixels, and wherem said graphics processor is configured to vary the density of the samples generated 81. The graphics system as recited m claim 80, wherem said graphics processor is configured to vary the density of the samples generated on a per-scan lme basis, a per-group-of-scan-lme basis, a per-region basis, a per- pixel basis, or a per-group-of-pixel basis 82. The graphics system as recited in claim 80, wherem said density is vaned accordmg to mput from a gaze trackmg device, an eye-tracking device, mput from a head-tracking device, mput from a hand-tracking device, mput from a mouse, a cursor position, a visible object position, or a mam character position. 83. The graphics system as recited m claim 80, wherem said sample-to-pixel calculation unit is configured to filter samples to form output pixels on a real tune basis. 84. The graphics system as recited in claim 80, wherem at least a part of each sample is double-buffered m said sample buffer 85. The graphics system as recited in claim 80, further compnsmg a sample position memory coupled to said graphics processor, wherein said sample position memory is configured to store one or more sample position schemes, and wherem said graphics processor is configured to read sample positions from said sample position memory. 86. The graphics system as recited m claim 80, further compnsmg a sample position memory coupled to said graphics processor, wherem said sample position memory is configured to store one or more sample position schemes for one or more sample densities, wherem said graphics processor is configured to read sample positions from said sample position memory accordmg to a selected sample density and a selected sample position scheme. 42 87. The graphics system as recited m claim 80, wherem said graphics processor is configured to store said samples mto said super-sampled sample buffer accordmg to bins, and wherem said bms correspond to screen space areas. 88 The computer graphics system as recited m claim 80, wherem said sample-to-p xel calculation unit is configured to select a variable number of samples from said sample buffer to filter mto each output pixel, wherem said variable number is related to the distance separating said output pixel from a pomt of foveation 89. The computer graphics system as recited m claim 88, wherem said vanable number is changeable on a per- frame basis, a per frame region basis, a per-pixel basis, a per-app cation basis, a per-scan lme basis, or a per group of scan lmes basis. 90 The computer graphics system as recited m claim 88, wherem said pomt of foveation is estimated based on a cursor position, a visual object generated by the graphics system, a mam character generated by the graphics system, or a predetermmed location on a display device 91 The computer graphics system as recited in claim 88, further compnsmg a gaze trackmg unit coupled to said graphics processor, wherem said graphics processor is configured to estimate one or more of said pomt of foveation based on data received from said gaze trackmg unit 92. The computer graphics system as recited m claim 91, wherem each of said one or more pomts of foveation conespond to a different eye. 93. The computer graphics system as recited m claim 91, wherem each of said one or more pomts of foveation corresponds to a different viewer. 94. The computer graphics system as recited m claim 91, wherem said gaze trackmg unit is a video camera, EMG sensor, an eye-and-head tracker, an eye tracker, a head tracker, a hand tracker, a data glove, a wand, a data suit, a body position sensor, an acoustic sensor, an mfrared sensor, a motion sensor, a pressure sensor, or a position sensor. 95. The computer graphics system as recited m claim 80, wherem said graphics processor is configured to generate samples accordmg to a stochastic distnbution, a perturbed regular grid, or a regular gnd. 96. The computer graphics system as recited m claim 80, wherem said graphics processor is configured to generate said plurality of samples accordmg to a sample density scheme, wherem said sample density scheme is programmable. 43 97 The computer graphics system as recited m claim 80, wherem said graphics processor is configured to vary the density of samples generated as a function of the x-offset and y-offset from the samples to one or more pomts of foveation. 98. The computer graphics system as recited in claim 80, wherem said graphics processor is configured to vary the density of samples generated on a scan lme basis 99. The computer graphics system as recited m claim 80, wherem said sample buffer comprises a plurality of regions, wherem each region has a particular sample density lOO.The computer graphics system as recited m claim 80, further compnsmg a sample position memory coupled to said graphics processor and said sample-to-pixel calculation unit, wherem said sample position memory is configured to store sample position mformation, wherem said sample position mformation is a pattern that is read by said graphics processor and used by said graphics processor to generate sample positions, and wherem said graphics processor is configured to use said sample positions to generate samples 101. The computer graphics system as recited m claim 100, wherem said sample position mformation compnses x- offsets and y-offsets 102. The computer graphics system as recited m claim 80, wherem each sample compnses mformation selected from the group consisting of one or more color values, an alpha value, a transparency value, a z-value, a blur value, an mtensity value, bπghter-than-bπght information, and sample control mformation. 103. The computer graphics system as recited m claim 95, wherem said sample buffer is configured to store more than one sample per output pixel. 104. The computer graphics system as recited in claim 80, wherem said sample-to-pixel calculation unit is programmable to select samples from said sample buffer that fall withm a constant-radius circular filter. 105. The computer graphics system as recited m claim 80, wherem said sample-to-pixel calculation unit is programmable to select samples from said sample buffer that fall withm a vanable extent filter, wherem said vanable extent vanes accordmg to the x-offset and y-offset from the center of said filter to a pomt of foveation. 106.The computer graphics system as recited m claim 95, wherem said sample-to-pixel calculation unit is programmable to select samples from said sample buffer that fall withm a vaπable extent filter, wherem said variable extent is programmable. 44 107. The computer graphics system as recited m claim 95, wherem said sample-to-pixel calculation unit is programmable to select samples from said sample buffer that fall withm a maximum x-offset and a maximum y-offset from the center of the pixel bemg calculated 108 A graphics system compnsmg: a sample position memory configured to store one or more sample position schemes, a graphics processor coupled to said sample position memory and configured to select one of said sample position schemes and configured to generate a plurality of samples accordmg to said selected sample position scheme; a sample buffer coupled to said graphics processor, wherem said sample buffer is configured to store said samples, wherem said sample buffer is configured to double-buffer at least a portion of said samples; and a sample-to-pixel calculation unit coupled to said sample buffer, wherem said sample-to-pixel calculation unit is configured to select one or more of said stored samples to filter mto an output pixel 109. The computer graphics system as recited m claim 108, wherem said sample-to-pixel calculation unit is programmable. 1 lO.The computer graphics system as recited m claun 108, wherem said sample position memory is programmable. 111.The computer graphics system as recited in claun 108, wherem said sample-to-pixel calculation unit is configured to filter said one or more selected samples mto pixels m real time 112. The computer graphics system as recited m claim 108, wherem said sample position memory is configured to store x and y coordmate mformation for each sample generated by said graphics processor 113. The computer graphics system as recited m claim 108, wherem said sample position memory is configured to store x and y coordmate mformation for each sample stored m said sample buffer. 114. The computer graphics system as recited m claim 108, wherem said sample position memory is configured to cycle through each of said plurality of sample position schemes m either a predetermmed order or a random order. 115. The computer graphics system as recited m claim 108, wherem said graphics processor is configured to read sample positions from a selected one of a plurality of sample position schemes stored in said sample position memory. 45 116. The computer graphics system as recited m claim 108, wherem said selected sample position scheme is selected randomly from the sample position schemes stored m said sample position memory. 117. The computer graphics system as recited m claim 108, wherem said selected sample position scheme is selected from among the sample position schemes stored m said sample position memory accordmg to a predetermmed order. 118. The computer graphics system as recited m claun 108, wherein said sample position schemes are selected from the group consistmg of the followmg- regular gnds, perturbed regular gnds, and stochastic. 119. The computer graphics system as recited m claim 108, wherem said sample position schemes are selected from the group consistmg of the followmg: regular gπds, perturbed regular grids, and stochastic 120.The computer graphics system as recited m claun 108, wherem said sample position memory compnses a memory table and hardware for unfolding said memory table accordmg to a number of different unfolding schemes. 121. The computer graphics system as recited m claim 108, wherem said sample position memory compnses a table of random numbers and a programmable state machme capable of generatmg a plurality of different gnd types, wherem said graphics processor is configured to utilize said random numbers as offsets from a selected one of said plurality of different gnd types. 122. The computer graphics system as recited in claun 108, wherein said sample position memory comprises a memory table stormg information usable to calculate repeatable sample positions. 123. The computer graphics system as recited m claim 108, wherem said information compnses x-offsets and y- offsets. 124.A method for rendenng objects with a computer graphics system, the method compnsmg- calculating a plurality of sample positions; generating a sample for each sample position; stonng the samples m a sample buffer, wherem at least a portion of the samples are at least partially double- buffered m said sample buffer; selectmg a plurality of stored samples; and 46 filtermg the selected plurality of samples to form an output pixel value m real time, wherem said filtermg is performed once per pixel per frame in real tune, wherem said output pixels are sent to duectly to a display device without bemg stored in a traditional frame buffer. 125. The method as recited m claim 124, wherem said calculatmg compnses specifymg each sample position accordmg to one of the following: a regular grid, a perturbed regular gnd, or a stochastic gnd. 126. The method as recited m claim 124 or 125, wherem said selecting comprises: determmmg a distance from a particular sample position to the center of a particular output pixel to be calculated; and comparmg the distance with a predetermmed filter extent. 127. The method as recited m claim 124 or 125, wherem said filtermg compnses: calculating a weighting factor for each selected sample, wherem the weightmg factor is related to the distance between the sample and the output pixel bemg calculated; and multiplying each sample pixel's color values with the weighting factor. 128. The method as recited m claim 124 or 125, wherem said filtermg compnses: calculatmg a weighting factor for each selected sample, wherem the weighting factor is related to the x- and y- offset between the sample and the output pixel bemg calculated; and multiplying each sample pixel's color values with the weightmg factor. 47

Inventors: DEERING MICHAEL F, NAEGLE N DAVID, NELSON SCOTT, DEERING, MICHAEL, F., NAEGLE, N., DAVID, NELSON, SCOTT
Applicants: SUN MICROSYSTEMS INC, SUN MICROSYSTEMS, INC.
Application year: 1999
Main classification: G06T15
IPC codes: G06T5, G06T11, G06T15