Source: https://patents.justia.com/patent/20130215235
Timestamp: 2020-04-09 21:42:42
Document Index: 74018641

Matched Legal Cases: ['§119', 'Application No. 61', 'art 500', 'art 500', 'art 900', 'art 900']

US Patent Application for THREE-DIMENSIONAL IMAGER AND PROJECTION DEVICE Patent Application (Application #20130215235 issued August 22, 2013) - Justia Patents Search
Justia Patents Multiple CamerasUS Patent Application for THREE-DIMENSIONAL IMAGER AND PROJECTION DEVICE Patent Application (Application #20130215235)
This application is a continuation-in-part of U.S. patent application Ser. No. 13/458956, filed on Apr. 27, 2012, and titled “THREE-DIMENSIONAL IMAGER AND PROJECTION DEVICE,” which claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Application No. 61/481,118, filed on Apr. 29, 2011, and titled “A MOBILE INTERACTIVE OPTICAL PROJECTION APPARATUS.” These prior applications are hereby incorporated by reference herein in their entirety.
A system for remotely powering an electronic device is disclosed herein. In some implementations, the system comprises: one or more sensors, the one or more sensors being configured to detect at least visible or invisible light from a field of view; one or more projectors, the one or more projectors being configured to project at least invisible light into the field of view; and one or more processors configured to control the one or more projectors to project at least one or more invisible light patterns into the field of view; analyze the invisible light detected by the one or more sensors in order to identify the location of an electronic device within the field of view; and control the one or more projectors to project a beam of electromagnetic radiation toward the identified location in the field of view in order to power the electronic device by wirelessly transferring energy to the electronic device.
A device for collecting multispectral data from a field of view is disclosed herein. In some implementations, the device comprises: one or more sensors, the one or more sensors being configured to detect light in two or more spectral bands, including light outside of the visible spectrum, from one or more fields of view, and to create one or more multispectral images of the one or more fields of view; one or more projectors, the one or more projectors being configured to project a light pattern into at least one of the one or more fields of view; and one or more processors configured to analyze the data in at least one of the spectral bands detected by the one or more sensors in order to generate depth data indicative of the depth of at least one item in at least one of the one or more fields of view; and combine the one or more multispectral images and the depth data to create multi-dimensional data of at least one of the one or more fields of view.
A 3D movie camera system is disclosed herein. In some embodiments, the 3D movie camera system comprises: one or more cameras, the one or more cameras being configured to detect visible light and invisible light from a field of view, and to create visible light images and invisible light images of the field of view; one or more projectors, the one or more projectors being configured to project invisible light into the field of view; and one or more processors configured to control the one or more projectors to project at least one or more invisible light patterns into the field of view; analyze the invisible light images detected by the one or more cameras in order to generate depth data indicative of the depth of at least one item in the field of view; combine the visible light images and the depth data to create three-dimensional data of the field of view; and execute a processing function on the three-dimensional data, the processing function being selected from the group comprising virtually moving the camera location, distinguishing the item in the field of view based on the depth data, adding a virtual light source, changing the depth of focus of the visible light images, three-dimensional content-aware fill, or creating a stereoscopic image of the field of view using at least two virtual cameras.
A three-dimensional imager and projection device is disclosed herein. In some implementations, the device comprises: one or more cameras, the one or more cameras being configured to detect visible light and invisible light from one or more fields of view, and to create one or more visible light images and one or more invisible light images of the one or more fields of view; one or more projectors, the one or more projectors being configured to project at least invisible light into at least one of the one or more fields of view; and one or more processors, the one or more processors being configured to control the one or more projectors to project at least one or more invisible light patterns into at least one of the one or more fields of view; analyze the one or more invisible light images detected by the one or more cameras in order to generate depth data indicative of the depth of at least one item in at least one of the one or more fields of view; and combine the one or more visible light images and the depth data to create three-dimensional data of at least one of the one or more fields of view, wherein the one or more invisible light patterns are dynamically adjusted so as to increase the resolution of the depth data in at least one portion of the field of view.
FIG. 10 illustrates an example embodiment of a device that can be used to collect 3D and multispectral information about an environment within a field of view.
Particular implementations of the subject matter described in this disclosure can have various potential advantages. For example, the devices described herein can be used to enhance a user's interaction with a real-world environment. Various implementations of the devices can be used to provide information (e.g., distance information, temperature information, object recognition, consumer information, such as ratings, value, etc.) about objects in a real-world environment. The devices can be used to facilitate communication between two users. In various implementations, the devices can be used to manipulate and/or interact with virtual objects, both on a surface and in space, in a real-world environment. For example, the device can be used to project a virtual keyboard on a surface, which can be used to control a computer. As another example, the user can provide gestures as an input which can be processed by the device to provide instructions (e.g., turn on/off, move, adjust the settings, etc.) to various electronic systems and instruments in the real-world environment. As yet another example, the device can be used to charge various electronic systems and instruments in the real-world environment. The device can be used to alter the appearance of objects in the real-world environment. Many other advantages and benefits can be provided by the devices described herein. For example, unlike conventional liquid crystal based display devices, the native resolution of the projected output is not fixed and accordingly the devices can advantageously display the generated output at various resolutions.
The input device 110 can include a plurality of sensors 110a and 110b that can receive information from the surrounding environment 120. The plurality of sensors 110a and/or 110b can include visible light cameras, infrared light cameras, charge coupled device detectors, CMOS detectors, or any other suitable sensor that uses one or more photodetectors to record light data (e.g., photodiodes, etc.), depending upon the choice of light sources in the optical projection module 105. The plurality of sensors 110a and 110b are configured to receive input information (e.g. visible light and invisible light) from the surrounding environment 120 within a field of view of the device 100. In some implementations, the sensor 110a can be a visible light camera adapted to receive visible light from the environment to form a visible light image (using one or more pixels) of the environment, while the sensor 110b can be an invisible light camera (e.g., an infrared camera) adapted to receive invisible light (e.g., infrared light) from the environment to form an invisible light image. In various implementations, the sensors 110a and 110b can be replaced by a single broadband sensor that can detect both visible and invisible light. The visible and invisible light detected by the single broadband sensor can be output as separate color data channels (e.g., multispectral data) and transmitted to the processing and control unit 115.
The processing and control unit 115 can include an electronic circuit that can execute a set of programmable instructions. In various implementations, the processing and control unit 115 can include a controller 115d to, for example, cause the optical projection module to project desired visible and invisible light patterns (which can consist of a single point or multiple points), as discussed herein. In various implementations, the processor can also include various modules that can process the information received by the input device 110. For example, the processor can include a depth data module 115a that can analyze input information to extract depth information, a 3D data module 115b that can generate 3D data of the environment in the field of view of the device 100, a gesture recognition module 115c that can detect and interpret gestures or other input from a user 100, etc. Other modules, such as tracking modules, object recognition modules, etc. can also be included. The processing and control unit 115 can also include one or more memory units 115e which can be accessed by, for example, the various modules 115a-115d of the processor. In various implementations, the one or more memory units 115e can include a set of executable instructions that can be executed by the processor. In various implementations, the processing and control unit 115 can also include a transceiver 115f that can transmit signals to and/or receive signals from the environment 120 or remote devices, as described herein. In various implementations, the modules 115a-115b can be implemented using one or more processors.
FIG. 2 illustrates an example implementation of the optical projection module 105 that can be used in some implementations of the device 100 illustrated in FIG. 1. In the illustrated implementation of the optical projection module, light from the various optical sources 105a-105d is combined using optical beam combiners 201a-201d into a single light output beam, of which light ray 203 is representative. In various implementations, the optical beam combiners 201a-201d can include dichroic filters, reflectors, beam splitters, waveguide based optical combiners, fiber-optic based optical combiners, etc., or any other component that would be suitable for directing, combining, or outputting light from the optical sources 105a-105d, depending upon the wavelengths of light provided by the sources. The combined light output 203 is reflected by a reflector 205 onto a scanning mirror 210. In various implementations, the scanning mirror 210 can include a mirror coupled to a motor (e.g. a servo motor, stepper motors, etc.), an electromechanical systems device such as, for example, a galvanometer, a piezo-electric device, etc. In some implementations, multiple scanning mirrors 210 of various sizes and locations can be used. In addition, in some implementations, some other type of scanning module besides a scanning mirror 210 can be used. For example, a scanning module can include prisms, diffraction gratings, and/or other optical components coupled to an actuator of suitable type.
In various implementations, the scanning mirror 210 can be adapted to steer the output beam in any direction to achieve full scanning capabilities of the environment in the field of view of the device. For example, when the scanning mirror 210 is in position B, the combined light output from the reflector 205 is directed out of the optical projection module as light beam 220, and can scan a first region 230 of the environment in the field of view. When the scanning mirror 210 is in position A, the combined light output from the reflector 205 is directed out of the optical projection module as light beam 215, and can scan a second region 235 of the environment in the field of view. In some implementations, the scanning mirror 210 raster scans the combined light output across a field of view, for example, with a relatively high refresh rate. In various implementations, each optical source 105a-105d can be individually modulated (e.g. turned on or off, dimmed, brightened, focus adjusted, spectrally modulated, etc.) by the processing and control unit 115 so as to create independent patterns (e.g., independent red, green, and blue visible patterns, and an independent invisible pattern, any of which may overlap) as the combined output beam is scanned across the field of view. In various implementations, the processing and control unit 115 can modulate each optical source 105a-105d to generate visible light patterns and invisible light patterns for various applications, as discussed herein. An optical projection module, such as illustrated in
FIG. 2, can have an advantage of not being limited to any particular native resolution, unlike, for example, some other projection systems.
The device 100 illustrated in FIG. 1 can be used in a variety of applications. For example, various implementations of the device 100 can be used in imaging applications to create, for example, 3D images, maps, representations, etc. of an environment within a field of view. Various implementations of the device 100 can also be used in augmented reality applications where visible light patterns (e.g. regular or irregular patterns, including any virtual objects, text, graphics, images, symbols, colors, etc.) are projected into a field of view to enhance and/or alter the surrounding environment. Various implementations of the device 100 can also be used in an interactive mode, as discussed herein, for example, with reference to FIGS. 4-6. In such implementations, an input from the user can be detected and processed by the device 100. The processing and control unit 115 can generate an output based on the user input, which output can be a visible pattern that is projected into the user's environment. Various implementations of the device 100 can also be used to identify an electronic device and to send a directed signal that can be used to turn on/off and/or charge the electronic device, as discussed herein, for example, with reference to FIGS. 8 and 9. Depending on any given application, the device 100 can have various modes of operation as discussed in greater detail below.
A variety of invisible light patterns can be projected into the environment within the field of view of the optical projection module 105 in order to determine depth data. In some implementations, the projected invisible light pattern is relatively static and is either constantly or repeatedly projected into the scene to gather depth data. In other implementations, the projected invisible light pattern is dynamic in that it can be changed from its previous state. In some implementations, the invisible light pattern can be changed frame-by-frame, every several frames, or over some other relatively short period of time as compared to changes in the locations of items in the field of view for a particular application. A dynamic invisible light pattern can be used in order to increase the resolution of the depth data. For example, in some embodiments, the invisible light pattern that is projected into the field of view is a binary pattern, such as an array of dots. In the case of, for example, a time-of-flight depth measurement system, a depth measurement can be collected for each location in a scene that corresponds to the location of a projected dot. If the pattern of projected dots remains relatively static, then depth data is collected for substantially the same locations within the scene over and over. In some implementations, however, the projected invisible light pattern (e.g., an array of dots) can be dynamically spatially shifted in time. For example, at a first time, the invisible light pattern can be projected in the field of view to collect a first set of depth data corresponding to the first set of locations within the field of view. Subsequently, at a second time, the invisible light pattern can be projected into the field of view such that it is shifted horizontally, vertically, and/or horizontally and vertically with respect to the pattern that was projected at the first time. In this way, the invisible light pattern that is projected at the second time can sample a second set of points within the field of view that is different from the first set of points. This can yield a second set of depth data which can be used to enhance the resolution of the composite depth data.
In some implementations, the projected invisible light pattern that is used to collect depth data can be varied dynamically using, for example, a feedback loop. The feedback loop can be responsive to a characteristic of the scene that is measured by, for example, the depth data module 115a. As an example implementation of such a feedback loop for dynamically adjusting the projected invisible light pattern, a first invisible light pattern can be projected at a first time in order to collect first depth data. The first depth data can be analyzed by the depth data module 115a in order to determine the distance of various objects within the scene. If a certain object is detected at a distance beyond some threshold, the projected invisible light pattern can be dynamically altered so that the distant object is sampled with greater resolution. In the case of an invisible light pattern that consists of an array of dots, the invisible light pattern can be dynamically adjusted such that the dots are provided more closely spaced in the specific vicinity of a distant object (and, similarly, less closely spaced in the vicinity of a nearby object). This can be advantageous because, if a uniform density binary pattern is projected, distant objects may be sampled with lower resolution than nearby objects due to the spreading of the projected pattern with distance. However, by using this type of feedback loop to adjust the density of the invisible binary pattern in different parts of the field of view, the projected invisible light pattern can be dynamically altered to, for example, to increase, decrease, and/or equalize the resolution of collected depth data at desired sub portions of the scene corresponding to nearby or distant objects. This type of feedback loop can also be used to increase, decrease, and/or equalize the resolution of collected depth data in regions where the depth of a point within the field of view changes rapidly (e.g., the change is greater than some predetermined threshold) with respect to adjacent points.
As discussed herein, in some implementations, the projected invisible light pattern is a binary pattern that consists of areas where the invisible light beam is “on” and other areas where the invisible light beam is “off”. In other implementations, however, the projected invisible light pattern can be analog or even a relatively uniform brightness throughout all or a substantial portion of the scene. A projected invisible light pattern having uniform brightness can be used to extract depth data by, for example, utilizing the following method. The invisible light pattern with uniform brightness can be projected into the field of view. Then, the response of objects (e.g., the reflection of the invisible light pattern by the objects) within the field of view to the uniform brightness pattern can be observed with the invisible light camera. The intensity of the invisible light will decrease with increasing distance within the field of view. Accordingly, objects that are closer to the invisible light projector will appear brighter in the image collected by the invisible light camera, while objects that are more distant will appear dimmer due to the reduced intensity of the uniform brightness pattern with increasing distance. Accordingly, the distance of an object within the scene can be determined by the brightness of the response of that object to the projected uniform invisible light pattern. Other sources of invisible light within the scene may interfere with the projected uniform brightness pattern, thus corrupting the measured depth data. However, this difficulty can be at least partially overcome by projecting and/or detecting only a narrow wavelength range of invisible light such that the detected light signal can rise above the noise floor of any other invisible light that is present in the scene from ambient sources within the same wavelength range. For example, a narrow bandwidth invisible light source can be used to project the invisible light pattern, and a narrow bandpass filter corresponding to the same narrow band can be positioned in front of the invisible light camera so as to only collect light having the wavelength(s) of the projected invisible light pattern. Difficulty with background ambient invisible light can also be at least partially overcome by disregarding the initial image intensity data, but taking into account the changes in image intensity data over time. For example, in one implementation, another method of depth extraction can be used to obtain the initial values such as structured lighting, after which the changes in image intensity are used to calculate depth data.
As discussed herein, binary invisible light patterns and uniform invisible light patterns can both be used in order to collect depth data from a scene. In some implementations, a binary invisible light pattern and a uniform invisible light pattern can be projected alternately, or can be superimposed and projected simultaneously. In this way, depth data determined from one of the invisible light patterns can be used to enhance the accuracy and/or resolution of depth data collected by the other invisible light pattern. For example, samples of depth data collected using a binary invisible light pattern consisting of an array of dots can be used to enhance depth data collected using a uniform invisible light pattern.
The depth data or image can be texture mapped, merged, and/or combined with the visible light image using software methods, by a processor in the camera or on a remote machine, to obtain a 3D digital map of the scene. This is distinct from conventional 3D movie cameras, which instead capture separate 2D images from different perspectives (e.g., left-eye and right-eye perspectives) using dual sets of 2D cameras and other accessories. In some implementations, multiple devices 105a-d and 110a-b, and/or the devices 105, 110, and 100 that comprise them, can be stationed at different locations/angular positions about the scene in order to collect data from multiple vantage points and enhance the 3D digital map of the scene. For example, a first device 100 could be stationed at the front of a scene, and a second device 100 could be stationed at the back of the scene, approximately 180° apart from the first device 100. These two devices 100 may jointly be able to collect enough data to create a complete 3D digital map of the scene. It should be understood, however, that any number of devices 100 could be used. Since conventional 3D movie cameras create a 3D effect by superimposing or combining left-eye and right-eye perspectives, the images obtained by conventional 3D filming methods are not actually 3D images of the scene and, accordingly, certain functions such as changing viewing perspective, changing the zoom, etc. may not be able to be performed in post-processing of the images. In contrast, the 3D image obtained from the device 100 is a 3D representation of the scene, including depth data for data points or voxels of the scene. This 3D representation can allow for enhanced post-processing techniques to be applied. Additionally, the 3D images from the device 100 can be post-processed to create separate left-eye and right-eye video streams which can be viewed as a 3D movie using conventional 3D movie projectors and glasses. For example, virtual cameras can be positioned at two or more vantage points within the 3D representation of the scene. The virtual cameras can be used to create images of the scene from their respective vantage points. The images of the scene from the two or more vantage points can then be combined to create virtual stereoscopic 3D images of the scene, as if done by a traditional stereoscopic 3D camera rig.
There are many post-processing techniques that can be applied to the 3D images from the device 100. For example, the 3D image of the scene obtained by the movie camera can be processed using software methods to alter the depth of field to any desired level. This feature can provide cost benefits over conventional 3D camera rigs, which may require expensive lenses or other equipment to change the depth of field, and even then may only be able to do so while filming. In addition, changes in the depth data of the voxels in the 3D image of the scene can be used to identify objects with increased precision and accuracy, for example, to differentiate foreground and background objects for video compositing purposes. This feature can replace chroma key compositing techniques, such as the “Green Screen” that is used in conventional compositing methods to identify the background in a scene. Eliminating the “Green Screen” can provide more realistic images or videos. This method of object or background identification can also advantageously shorten the amount of filming time. Post-processing of the 3D image obtained by the movie camera (e.g., device 100) can be used to add different types of virtual set lighting (e.g., directional virtual set lighting from any perspective with proper shadow placement, virtual set lighting at any location within the scene, etc.) to the captured 3D image of the scene in order to simulate real-world lighting. Post-processing of the 3D image can also allow for other enhancements. For example, since the information captured by the device 100 includes 3D data of the scene, software post-processing algorithms can be used to manipulate the 3D data of the scene to provide special effects such as altering the effective camera placement by zooming in or out, or changing the viewing perspective. Expensive camera rigs, dollies, cranes, etc. are typically required to achieve these effects using conventional 3D filming techniques.
As just discussed, the depth data can be used to distinguish an object in the 3D scene by using the depth data. For example, the depth data can be analyzed to find locations within the scene where the distance to a detected object changes rapidly as a function of a transverse dimension in the scene, or where the change in depth data exceeds a threshold. By using this technique, any object can be isolated, masked, or cropped from the scene. Any such object that is identified in the scene by using the depth information can then be added to a library of 3D virtual objects. Any missing data from the 3D model of the object can be filled in using a content aware fill algorithm. Just as objects can be cropped from the scene, objects from the library of 3D objects can also be added to the scene as virtual objects.
In some implementations, the device 100, when operating in mode of operation 300 as a 3D camera, can be a stand-alone device. In some implementations, however, an existing camera can be modified to perform the functions described herein. For example, an accessory that is capable of projecting an invisible light pattern, as discussed herein, can be attached to an existing camera. The accessory could include an infrared laser diode, or some other invisible light source. In some implementations, the accessory can be designed to connect into the camera's hot shoe connector. The accessory can be controlled by the camera's existing processor.
In addition, the existing image sensor of the camera can be adapted to provide an invisible light image in addition to the visible light images it is already capable of producing. The invisible light patterns that are output by the invisible light projector accessory can be imaged by the camera's lens onto the camera's existing image sensor. The image sensor may include a Bayer filter. The Bayer filter includes a mosaic of small red, green, and blue filter elements in front of the sensor pixels. In many typical cameras, the sensor pixels corresponding to the blue and red filter elements are used to detect chrominance of the image, while the sensor pixels corresponding to the green filter elements (which are twice as numerous as the blue and red filter elements) are used to detect luminance. A typical square of four filter elements in a Bayer filter can include one blue filter element, one red filter element, and two green filter elements. The firmware of the camera can be reconfigured such that luminance is detected using one green filter element instead of two. The remaining green filter element can then be used in conjunction with the blue filter element to detect chrominance. Finally, in the case where the invisible light is infrared light, the red filter element can be used to detect the invisible light because the red filter element is at least partially transmissive to infrared light. In this way, the visible and invisible images can be collected substantially simultaneously using the image sensors of existing cameras, although this technique may decrease the image resolution. In other implementations, the existing camera can operate at a rate greater (e.g., 2×) than its normal frame rate (e.g., 60 frames per second instead of 30 frames per second). The existing image sensor can then be used to detect visible light images in addition to invisible light images (e.g., using the sensor pixels corresponding to red filter elements) in the frames where an invisible light pattern is present. In this type of implementation, the full resolution of the image sensor can be maintained for visible light images.
The mode of operation 301 illustrated in FIG. 3B can be employed in, for example, implementations of the device 100 that are used for augmented reality applications. Some of the functions performed in the mode of operation 301 can be generally similar to the functions performed in the mode of operation 300. In the illustrated mode of operation 301, the device 100 projects visible and/or invisible (e.g., infrared) radiation patterns into the environment in the field of view of the device 100, as shown in block 306, using the optical projection module 105. Visible and invisible light images of the environment in the field of view are obtained, as shown in block 310. The visible and invisible light images may be obtained by using the sensors 110a and 110b (e.g., a visible light camera and an invisible light camera, such as an infrared camera). Depth data is extracted from, for example, the invisible light images, as shown in block 312, and as discussed herein. The depth data can then be combined with the visible light images to obtain 3D data of the environment in the field of view, as shown in block 315, and as discussed herein.
FIG. 5 is a flowchart 500 that illustrates certain operations performed by the device illustrated in FIG. 4 while in the interactive mode. Some of the blocks of the flowchart 500 can be generally similar to the blocks depicted in FIGS. 3A and 3B. In block 505 the device 100 is adapted to project visible and/or invisible radiation patterns into the field of view. The device obtains visible and invisible light images of the user and the environment in the vicinity of the user, as shown in block 510. In various implementations, the visible light image also includes the visible radiation pattern projected by the device 100. As shown in block 512, depth data is obtained from the invisible image, as discussed herein. The depth data is combined with the visible light image to obtain 3D data of the user and the environment surrounding the user, as shown in block 515. The depth data and/or the 3D data is processed to identify user input, as shown in block 520. Identification of user input can be done using, for example, gesture recognition algorithms, facial recognition algorithms, object recognition algorithms, object tracking algorithms, etc. In some implementations, to reduce processing time, the 3D data obtained at one point in time can be compared with previously-obtained obtained 3D data to identify only those portions of the user and the surrounding environment that have changed. Processing only those portions of the user and the surrounding environment that have changed may reduce processing time.
The device 100 in the interactive mode can be used in a variety of applications. For example, the device 100 can be used to project an interactive graphical computer interface onto a surface (including a body part, such as a hand). The device 100 can also project a virtual keyboard or mouse pad, for controlling the graphical computer interface, onto a surface in the vicinity of the user. The user can then interact with the virtual keyboard or mouse pad by, for example, moving his or her finger (or some pointing object) on, or in proximity to, the surface on which the virtual keyboard or mouse pad is projected. The user's inputs can be identified based upon, for example, the 3D map of the user and his or her environment that is created at block 515. The user's inputs can be used to perform or control various functions through the graphical computer interface. For example, as shown in blocks 525 and 530 of FIG. 5, the user's inputs can be used to control a visible radiation pattern that is projected into the user's environment as part of the graphical computer interface. This visible radiation pattern could be, for example, a mouse pointer whose position on the graphical user interface is based on the user's movements on the virtual mouse pad. In addition, various user gestures could be defined to control actions of a device, such as, in the case of a computer, executing a mouse click, executing a program, etc. In some implementations, a virtual touchscreen display could be provided. For example, the device 100 could project an image of a display screen onto a surface. The user could then touch locations on the surface in order to execute various functions as if the surface were a touchscreen display. The locations of the user's touches can be determined from the 3D data. In some implementations, a user could also use gestures to indicate the location on the surface to project a virtual display. The user could also re-size or move the virtual display on the surface with gestures. Interactive gestures can be performed anywhere within the detected field of view of the device, and are not limited to the specific locations where the virtual display is projected.
In various implementations, the eyewear 600 can be a portion of a head mounted display. For example, visible patterns (virtual objects, text, graphics, images, symbols, colors, etc.) can be projected into the eyes by the optical projection module 105 by reflecting off of the lens surfaces 601a and 601b. The lens surfaces 601a and 601b can be at least partially transmissive to visible light so as to permit the user to see through the lenses. However, the lens surfaces 601a and 601b can also be designed to be partially reflective to visible light so that they can reflect a projected visible radiation pattern onto the user's retinas. For example, the lens surfaces of the eyewear can be treated with, for example, narrowband trichroic reflectors that correspond with the wavelengths of a color laser projector (e.g., the narrowband trichroic reflectors could reflect a narrow range of light around the red, green, and blue wavelengths of a color laser projector). Such trichroic reflectors would allow light from a color laser projector to be reflected off of the inner lens surfaces and into the eyes while still permitting the user to see through the lenses to observe the forward field of view. The lens surfaces can be curved in such a manner that laser beams from one or more optical projection modules 105 mounted on the eyewear (for example, a separate module for each lens) are reflected by the lens surfaces and into the eyes to form the visible radiation pattern directly on the retinas. In these implementations, the eyewear 600 and the optical projection module 105 can together function as a retinal projection display device. In such implementations, the characteristics of the projection beams and the distance between the lens surfaces 601a and 601b and the eye can be selected to provide a diffraction-limited system that can provide high quality images using the retinal projection feature. In some implementations, the lenses of the eyewear can include optical coatings to cause the lens surfaces to be substantially reflective to the visible wavelengths used by the projection module, while being substantially transmissive to other wavelengths of visible light. In some implementations, the lenses may be active-matrix organic light-emitting diode (AMOLED) displays, which can be configured to be transmissive or to display information to the user.
FIG. 7 illustrates an example implementation of the device 100 illustrated in FIGS. 1 and 4 that includes a retinal projection feature. The device 100 illustrated in
FIG. 7 functions similar to what has been described elsewhere herein, except that the optical projection module 105 can be configured to project the visible radiation pattern (e.g., a virtual object, text, graphics, images, symbols, color patterns, etc.) directly into each eye of the user 125. The device 100 can be configured such that the visible radiation pattern is projected into the user's eye while the invisible radiation pattern is projected into the environment surrounding the user to generate 3D data of the user and the surrounding environment. For example, in some implementations, when the scanning mirror 210 of the optical projection apparatus is directed about a first direction, the visible radiation pattern is projected into the user's right eye with beam 705, and subsequently when the scanning mirror 210 is directed about a second direction, the visible radiation pattern projects into the user's left eye with beam 710. In this example, the beams 705 and 710 originate from a common scanning mirror 210. In other implementations, multiple beams originating from different scanning mirrors 210, or different projection modules, can be projected into the user's eyes. For example, multiple projection modules could be used to allow for retinal projection to users in a 360 degree field of view. Additionally, multiple scanning mirrors of various sizes and locations can be used in succession. In various implementations, the device 100 may be configured to track the user's eyes, for example, based on the 3D data, so that the visible radiation pattern can be projected into the user's eye repeatedly over time.
FIG. 8 illustrates an example implementation of a device 100 that can be used to turn on/off or charge electronic objects in the surrounding environment. As discussed herein, the device 100 can also be used to transmit data to an electronic object in the surrounding environment. The implementation of the device 100 illustrated in FIG. 8 can be similar to those described elsewhere herein. However, the device 100 illustrated in FIG. 8 can include a steerable, directional source of radiation. In some implementations, the directional source of radiation is the optical projection module 105 (which includes the sources 105a-105d that are steered with the mirror 210). In other implementations, a separate steerable, directional radiation source 800 can be provided. The radiation source 800 can be structurally and functionally similar to the optical projection apparatus 105. The optical projection module 105 or directional source of radiation 800 can be used, for example, to wirelessly transfer power to charge an electronic device located within the field of view of the device 100, and/or power the device in real time. The optical projection module or the directional source of radiation 800 can be configured, for example, to emit electromagnetic radiation in the visible, infrared, terahertz, RF, or microwave spectral regions. The electronic device towards which the electromagnetic radiation emitted by the source 800 is directed can be received by a photodiode (e.g. a semiconductor based photovoltaic cell) included in the electronic device and converted into usable electricity. In addition, the electronic device being charged/powered can also include an array of photodiodes (e.g., an array of independent photodiodes, a CMOS/CCD camera, etc.) that is capable of, for example, resolving changes in the spatial profile of the beam of electromagnetic radiation. This capability can be used to receive data transmissions, as discussed herein.
FIG. 9 is a flow chart 900 illustrating an example method of turning on/off or charging electronic objects in the surrounding environment. Some of the elements of the flowchart 900 can be generally similar to the elements depicted in FIGS. 3A and 3B. As discussed herein, the device 100 generates 3D data of the environment in the field of view by performing operations described in blocks 305, 310, 312 and 315. The 3D data can be processed and analyzed by the processing and control unit 115 to identify electronic objects (e.g. phones, televisions, gaming consoles, etc.) that can be turned on/off or charged, as shown in block 910. In various implementations, other methods of identifying electronic objects can be employed, such as, for example, wireless communication feedback from the electronic object (e.g., using an ad-hoc/WWAN network, etc.). A beam of electromagnetic radiation from the radiation source 105, 800 can then be directed towards the identified electronic device to charge the device, as shown in block 915. In some cases, the wireless power transfer described herein may not necessarily be limited to line-of-sight beam paths. This may be true, for example, if terahertz radiation is used for the charging beam, since such radiation can propagate through certain materials. The power level of the charging beam, and/or an available light source with the most efficient properties (e.g., wavelength) for power transfer to a particular device, can be selected based on wireless communications with the remote electronic device. In addition, information, such as on/off commands, or data, can be provided to the electronic device via the beam of electromagnetic radiation by modulating the beam. For example, the spatial, temporal, spectral, polarization, and/or output power of the electromagnetic beam, or of a plurality of beams, can be modulated to transmit data to the electronic device. In the case where the optical projection module 105 includes multiple light sources at different wavelengths, and/or a single light source capable of producing light of multiple wavelengths, data transfer with wavelength division multiplexing could be performed. In some implementations, the remote electronic device has an array of one or more photodetectors (e.g, photodiodes, photovoltaic cells, Coherent Perfect Absorbers, etc.) designed or optimized to the spectrum of the beam of electromagnetic radiation that is powering the electronic device and/or transmitting data to the electronic device. In some implementations, the electronic device that is being powered can also include an instance of the device 100 (or any of the sub-components thereof). In such implementations, the electronic device can transmit data back to the device 100 that it is being powered by, and the data can be received, for example, by the sensors 110a-b (e.g., visible and/or invisible light cameras). This data can also be transferred by modulating a beam of electromagnetic radiation. The device 100 can receive the data using, for example, its one or more cameras.
FIG. 10 illustrates an example embodiment of a device 1000 that can be used to collect 3D and multispectral information about an environment within a field of view. The device 1000 can be similar to those illustrated in FIGS. 1 and 2 (e.g., device 100). For example, the device 1000 can include an optical projection module 1005 having optical sources 1005a-d. These can be, for example, red, green, blue, and infrared laser diodes. The outputs of these optical sources can be combined and scanned across a field of view using a scanning mirror 1210, as described herein with respect to FIG. 2. The device 1000 can also include an image sensor 1010. The image sensor 1010 can receive incoming light 1050 from the field of view via the scanning mirror 1210 and the reflectors 1205. The incoming light 1050 from the field of view can be scanned across the image sensor 1010 by the scanning mirror 1210 just as the output beam from the optical sources 1005 is scanned across the field of view.
The incoming light 1050 can also be passed through a dispersive optical element 1060, such as a prism or a diffraction grating. The dispersive optical element 1060 can separate the incoming light 1050 into its spectral components 1060, including one or more spectral components outside the visible spectrum. The spectral components 1070 are then incident upon the image sensor 1010 and can be recorded for each resolvable point within the field of view. If, for example, the spectral information is collected for a line of points in the field of view at a time, then each line of sensor pixels in one dimension corresponds to one of the points from the field of view, while corresponding sensor pixels in the perpendicular direction record the spectral data for each point. The scanning mirror 1210 can then be operated to collect the spectral data for a subsequent line of points in the field of view. Though not illustrated, the scanning mechanism can also include a slit for limiting the incoming light 1050 to a line of points from the field of view at the time. In this way, the spectral signature of each point in the field of view can be measured along with the depth and color information already discussed herein. By collecting multispectral data, including one or more spectral components outside the visible spectrum, for each point in the field of view, it may be possible, for example, to identify objects in the field of view based upon their unique spectral signature. In some implementations, the device 1000 can also be used to collect hyperspectral information from one or more points in the field of view. The device 1000 can be used to project light to a location or subset of space in one or more fields of view, including for any of the reasons and/or applications discussed herein with regard to any other device.
A multispectral time of flight imaging system can be implemented. For example, a pulsed light source can be used to emit light pulses that are scanned across a field of view using a scanning mechanism. The pulsed light emitted in a particular direction can be backscattered from the surrounding environment within the field of view. The pulsed light can be collected, and optionally passed through a dispersive optical fiber to stretch out the pulse in the time domain. The backscattered light pulse from each direction can be recorded by a photodetector. Then, a Fourier transform can be performed on the recorded time domain data for each pulse in order to extract the spectral information for each sampled point within the field of view. In addition, the round-trip time of flight for each pulse can be determined in order to extract depth data.
1. A system for remotely powering an electronic device, the system comprising:
one or more sensors, the one or more sensors being configured to detect at least visible or invisible light from a field of view;
one or more projectors, the one or more projectors being configured to project at least invisible light into the field of view; and
one or more processors configured to control the one or more projectors to project at least one or more invisible light patterns into the field of view; analyze the invisible light detected by the one or more sensors in order to identify the location of an electronic device within the field of view; and control the one or more projectors to project a beam of electromagnetic radiation toward the identified location in the field of view in order to power the electronic device by wirelessly transferring energy to the electronic device.
one or more sensors, the one or more sensors being configured to detect light in two or more spectral bands, including light outside of the visible spectrum, from one or more fields of view, and to create one or more multispectral images of the one or more fields of view;
one or more projectors, the one or more projectors being configured to project a light pattern into at least one of the one or more fields of view; and
one or more processors configured to analyze the data in at least one of the spectral bands detected by the one or more sensors in order to generate depth data indicative of the depth of at least one item in at least one of the one or more fields of view; and
combine the one or more multispectral images and the depth data to create multi-dimensional data of at least one of the one or more fields of view.
16. A 3D movie camera system comprising:
one or more cameras, the one or more cameras being configured to detect visible light and invisible light from a field of view, and to create visible light images and invisible light images of the field of view;
one or more projectors, the one or more projectors being configured to project invisible light into the field of view; and
one or more processors configured to control the one or more projectors to project at least one or more invisible light patterns into the field of view;
analyze the invisible light images detected by the one or more cameras in order to generate depth data indicative of the depth of at least one item in the field of view;
combine the visible light images and the depth data to create three-dimensional data of the field of view; and
execute a processing function on the three-dimensional data, the processing function being selected from the group comprising virtually moving the camera location, distinguishing the item in the field of view based on the depth data, adding a virtual light source, changing the depth of focus of the visible light images, three-dimensional content-aware fill, or creating a stereoscopic image of the field of view using at least two virtual cameras.
one or more processors, the one or more processors being configured to control the one or more projectors to project at least one or more invisible light patterns into at least one of the one or more fields of view;
combine the one or more visible light images and the depth data to create three-dimensional data of at least one of the one or more fields of view, wherein the one or more invisible light patterns are dynamically adjusted so as to increase the resolution of the depth data in at least one portion of the field of view.
Patent Grant number: 8760499
Application Number: 13/842,421