Abstract:
Systems, devices and methods are described including receiving a depth image and applying a template to pixels of the depth image to determine a location of a human head in the depth image. The template includes a circular shaped region and a first annular shaped region surrounding the circular shaped region. The circular shaped region specifies a first range of depth values. The first annular shaped region specifies a second range of depth values that are larger than depth values of the first range of depth values.

Description:
BACKGROUND 
       [0001]    Depth imaging technology has advanced dramatically over the last few years. Pixels in a depth image indicate calibrated depth in the scene, rather than a measure of intensity or color. Depth images may allow for more accurate detection of objects such as human beings. Further, detection or localization of a human head may aid the detection of other human body parts in an image such as shoulders, torso, arms and legs, and so forth. 
         [0002]    Most of the current approaches to human head location, like color-based methods and face detector based methods, utilize either color or grayscale intensity information. Moreover, face detection techniques are of no avail when the subject is not facing the camera. While, skin color detection techniques may be useful for locating other parts of the body, such techniques have difficulty adapting to varying illumination. Recent attempts at human body part detection based only on depth information are problematic when a subject&#39;s hands are closed and/or when the subject&#39;s head is partially or fully occluded by another body part (e.g., as may occur when a subject is bending forward). In addition, to train, object detectors, conventional depth-based techniques tend to require detailed 3D human pose images that are difficult to acquire. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0003]    The material described herein is illustrated by way of example and not by way of limitation in the accompanying figures. For simplicity and clarity of illustration, elements illustrated in the figures are not necessarily drawn to scale. For example, the dimensions of some elements may be exaggerated relative to other elements for clarity. Further, where considered appropriate, reference labels have been repeated among the figures to indicate corresponding or analogous elements. In the figures: 
           [0004]      FIG. 1  is an illustrative diagrams of an example head detection system; 
           [0005]      FIG. 2  is a flow chart of an example head detection process; 
           [0006]      FIGS. 3 and 5  illustrate an example head detection template: 
           [0007]      FIG. 4  is an illustrative diagram of an example head detection model; 
           [0008]      FIG. 6  is a flow chart of an example head detection process; and 
           [0009]      FIG. 7  is an illustrative diagram of an example system all arranged in accordance with at least some implementations of the present disclosure. 
       
    
    
     DETAILED DESCRIPTION 
       [0010]    One or more embodiments or implementations are now described with reference to the enclosed figures. While specific configurations and arrangements are discussed, it should be understood that this is done for illustrative purposes only. Persons skilled in the relevant art will recognize that other configurations and arrangements may be employed without departing from the spirit and scope of the description. It will he apparent to those skilled in the relevant art that techniques and/or arrangements described herein may also he employed in a variety of other systems and applications other than what is described herein. 
         [0011]    While the following description sets forth various implementations that may be manifested in architectures such system-on-a-chip (SoC) architectures for example, implementation of the techniques and/or arrangements described herein are not restricted to particular architectures and/or computing systems and may be implemented by any architecture and/or computing system for similar purposes. For instance, various architectures employing, for example, multiple integrated circuit (IC) chips and/or packages, and/or various computing devices and/or consumer electronic (CE) devices such as set top boxes, smart phones, etc., may implement the techniques and/or arrangements described herein. Further, while the following description may set forth numerous specific details such as logic implementations, types and interrelationships of system components, logic partitioning/integration choices, etc., claimed subject matter may be practiced without such specific details. In other instances, some material such as, for example, control structures and full software instruction sequences, may not be shown in detail in order not to obscure the material disclosed herein. 
         [0012]    The material disclosed herein may be implemented in hardware, firmware, software, or any combination thereof. The material disclosed herein may also be implemented as instructions stored on a machine-readable medium, which may be read and executed by one or more processors. A machine-readable medium may include any medium and/or mechanism for storing or transmitting information in a form readable by a machine (e.g., a computing device). For example, a machine-readable medium may include read only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.), and others. 
         [0013]    References in the specification to “one implementation”, an “implementation”, “an example implementation”, etc., indicate that the implementation described may include a particular feature, structure, or characteristic, but every implementation may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same implementation. Further, when a particular feature, structure, or characteristic is described in connection with an implementation, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other implementations whether or not explicitly described herein. 
         [0014]      FIG. 1  illustrates an example system  100  in accordance with the present disclosure. In various implementations, system  100  may include a head detection module  102 , a database  104 , and a network  106 . As will be explained in greater detail below. detection module (HDM)  102  may receive a depth image  108  that includes a foreground portion  110  (e.g., in the form of an image of a human being) and background portion  112 . In various implementations, depth image  108  may have been preprocessed using various well-known techniques (see, e.g., Azriel Rosenfeld and John L. Pfaltz, “Sequential Operations in Digital Picture Processing,”  J. ACM , vol. 13, no. 4, pp. 471-494, October 1966) to segment image  108  into foreground portion  110  and background portion  112  and/or to identify foreground portion  110  as the image of a human body. 
         [0015]    In various implementations, HDM  102  may receive depth image  108  and a head template  114 . HDM  102  may then apply head detection processes to be described in greater detail below to detect and locate a human head in depth image  108  using template  114 . In various implementations, HDM  102  may receive depth image  108  directly, may receive depth image  108  via network  106 , and/or may receive depth image  108  from database  104  either directly or via network  106 . Similar possibilities apply to the reception of the head template. In various implementations, HDM  102  may provide results of the head detection processes including the pixel location within the depth image corresponding to the center of a detected head and the detected head&#39;s radius value to be stored in database  104  either directly or via network  106 . 
         [0016]    In various implementations, depth image  108  may be a monochrome or color depth image including pixels specifying chrominance and/or luminance intensity data values and depth data values. For example, depth image may include a two-dimensional (2D) array of image intensity values (e.g., luminance values) at image pixel positions (x,y) with each pixel position also including a depth (z) value. Further, depth image  108  lay have any resolution and/or aspect ratio. The present disclosure is not limited to any particular data format, image resolution, image aspect ratio and so forth associated with depth image  108 . In addition, network  106  may be any type network and may include any combination of wireless and/or wired network technology. For instance, in a non-limiting example, network  106  may include one or more wireless local area networks (LANs) in combination with a wide area network (WAN), such as the internet. 
         [0017]    HDM  102  may be provided by any computing system. For example, HDM  102  may be provided by a computing system that also captured depth image  108 . In other implementations, HDM  102  may be remote to any device that captured image  108 . For example, one or more processor cores of a remote server computing system may provide HDM  102 . Further, any type of logic including hardware, software and/or firmware logic or any combination thereof may HDM  102 . 
         [0018]      FIG. 2  illustrates a flow diagram of an example process  200  for detecting a head in a depth image according to various implementations of the present disclosure. Process  200  may include one or more operations, functions or actions as illustrated by one or more of blocks  202 ,  204 ,  206 ,  208 ,  210  and  212  of  FIG. 2 . By way of non-limiting example, process  200  will be described herein with reference to example system  100  of  FIG. 1 . 
         [0019]    Process  200  may begin at block  202  where a foreground pixel in depth image  108  may be selected. For example, referring to  FIG. 1 , depth image  108  of block  202  may have been preprocessed using well-known techniques to specify the depth image&#39;s pixels as belonging to either background portion  112  or foreground portion  110 . In addition, the preprocessing may have identified portion  110  as a human body. Block  202  may thus include selecting a pixel from foreground portion  110 . 
         [0020]    At block  204 , a determination may be made as to whether the foreground pixel selected at block  202  is adjacent to a body border. For example, in  FIG. 1 , pixels  118  residing within body boundary  120  are specified as foreground pixels while pixels  122  residing outside body boundary  120  are specified as background pixels. Block  204  may then involve determining if the selected foreground pixel is near by or next to a body border. In various non-limiting implementations, a foreground pixel selected at block  202  may be designated as not being adjacent to a body border if there are two or more pixels in either the horizontal or vertical directions separating the selected pixel from a body border. 
         [0021]    If block  204  results in a determination that the pixel selected at block  202  is adjacent to a body border, then process  200  may loop back to block  202  and a next foreground pixel may be selected and another iteration of block  204  may be undertaken With that pixel. If however, block  204  results in a determination that the pixel selected at block  202  is not adjacent to a body border, then process  200  may continue at block  206  where head template  114  may he applied to the selected foreground pixel to perform template matching. 
         [0022]    In various implementations, the head template  114  applied at block  206  may include an array of points having a pitch and orientation that matches the pitch of depth image  108 &#39;s pixel array so that each point in the template corresponds to one pixel location in the depth image. In other implementations, the pitch of head template  114  may be an integer multiple of the pitch of the depth image. In addition, head template may have any size and or shape. 
         [0023]    Further, the size of head template may adapt as head template  114  is applied to depth image  108 . For instance, while in the non-limiting example implementations that follow, head template  114  may he described as circular shaped array of diameter having an initial diameter sufficient to span nine pixel locations in depth image  108  and having a total of fifty-three points, when applied to image  108 , head template  114  may be varied in diameter such that it may span any number of pixels.  FIG. 3  illustrates an overall shape  300  of an example head template  114  according to various implementations of the present disclosure. In this example, template  114  is circular in shape and has an initial radius R such that it includes an array of fifty-three points  302  (including a center point  304 ), where array  302  has a same pitch and orientation as the pixel array of image  108 . 
         [0024]    In various implementations, head template  114  may be created in reference to a projection model. For instance,  FIG. 4  illustrates a reference projection model  400  according to various implementations of the present disclosure.  FIG. 4  shows two views  402  and  404  of model  400 . In view  402 , a spherical object  406  having a radius R and modeling a human head appears viewed side-on with respect to a view plane  408  representing, for instance, an image plane of depth image  108 . In view  404 , object  406  is shown from the perspective of the view plane  410 . In both views  402  and  404 , an ordinate Z (orthogonal to view plane  410 ) represents increasing depth or distance away from view plane  410 . 
         [0025]      FIG. 4  depicts several points A, B, and C on the surface of object  406  and corresponding projections of those points A′, B′, and C′ on view plane  410 . Point C represents a closest point on object  406  with respect to view plane  410 , point A represents a furthest visible point, and point B represents a location having an intermediate depth or distance between point A and point C. The distance between the projection points B′ and C′ is denoted by r. Assuming that the distance AA′ is M, then the distance CC′ is M-R, and a depth value associated with B′ may be calculated using the following formula: 
         [0000]    
       
         
           
             
               
                 
                   
                     B 
                     depth 
                     ′ 
                   
                   = 
                   
                     
                       
                         
                           
                             R 
                             2 
                           
                           - 
                           
                             r 
                             2 
                           
                         
                       
                       R 
                     
                     . 
                   
                 
               
               
                 
                   ( 
                   1 
                   ) 
                 
               
             
           
         
       
     
         [0000]    Using Eqn. (1), the depth of any point on the surface of the sphere that projects onto view plane  410  of a depth image, and hence the depth value associated with the projection of that point on the depth image view plane, may be determined. 
         [0026]    However, it may be recognized that, in general, the center portion of a human head in a depth image will be closer to the image view plane, marginal portions of the head will be somewhat further away from the view plane, and that background portions of the image (e.g., non-head body parts, background objects, and so forth) will be yet further away from the view plane. With this in mind, a head template in accordance with various implementations may be specified to include three concentric regions having different depth values associated with each circle. 
         [0027]    For instance, in various implementations, the structure of head template  207  may be specified as a set of a three concentric circular an/or annular shaped regions.  FIG. 5  illustrates a head template model  500  viewed from the perspective of a depth image plane according to various implementations of the present disclosure. For example, head template  114  may he based on head template model  500 . As shown in  FIG. 5 , head template model  500  includes three regions: a circular inner region (IR)  502 , an annular shaped middle region (MR)  504 , and an annular shaped outer region (OR)  506 . 
         [0028]    In general a human head may have a radius R H  ranging from 80 mm to 150 mm. The projection of the head&#39;s radius in the image view plane may be denoted Rp. In model  500 , inner region IR represents the center of the head and has a radius of Rc=(4/5)•Rp, the annular shaped middle region MR represents the margin region of the head, and the annular shaped outer region OR represents a region adjacent to the head and has a radius of (5/4)•Rp. Expressed another way, region MR may have a radius that is 1.25 times larger than the radius of region IR and, in turn, region OR may have a radius that is 1.25 times larger than the radius of region MR. 
         [0029]    With M(x,y) representing the center of the model, M(i,j) represents a point on the model whose distance to M(x,y) may be provided by d=√{square root over (i−x) 2 +(j−y) 2 )}{square root over (i−x) 2 +(j−y) 2 )}. The following formulae may be used to determine the depth values of any point M(i,j) within the different regions IR, MR and OR: 
         [0000]    
       
         
           
             
               
                 
                   
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         [0000]    where Num(X) represents the total number of template points within the corresponding region X. 
         [0030]    Continuing the discussion of block  206 , template matching may include applying a head template to the selected foreground pixel by centering the template on the selected pixel location (e.g., corresponding to point M(x,y) in the template model) and then comparing the depth values of pixels neighboring the selected pixel to the template depth values in the different regions IR ( 502 ), MR ( 504 ) and OR ( 506 ) as determined using Eqns. (2), (3) and (4), respectively. 
         [0031]      FIG. 6  illustrates a flow diagram  600  of block  206  of process  200  in eater detail according to various implementations of the present disclosure. Process  600  may include one or more operations, functions or actions as illustrated by one or more of blocks  602 ,  604 ,  606 ,  608  and  610  of  FIG. 6 . 
         [0032]    Process  600  may begin at block  602  where head template  114  may be centered on the selected foreground pixel  601 . At block  604  the template radius may be varied from a minimum value (minR) to a maximum value (maxR) in predetermined step sizes for the foreground pixel  601  (denoted I(i,j) below) to determine a sample radius R p  using the following formulas: 
         [0000]    
       
         
           
             
               
                 
                   
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         [0000]    where values of the thresholds th inner , and th mid  and th determine the sample radius. 
         [0033]    With a sample radius determined at block  604 , process  600  may continue at block  606  where pixels neighboring the selected foreground pixel (corresponding to pixels {I(i,j)|√{square root over ((i−x)+(j−y))}{square root over ((i−x)+(j−y))}≦R p +R p /4}) may be associated with or divided among the different template regions. In various implementations, block  606  may be undertaken using the following equations: 
         [0000]        IR   p   ={I ( i,j )| d≦R   c &amp;  I ( i,j )&gt;th inner }
 
         [0000]        MR   p   ={I ( i,j )| R   c   &lt;d≦R   p &amp; I ( i,j )≧ th} 
 
         [0000]        OR   p   ={I ( i,j )| R   p   &lt;d ≦( R   p /4)&amp; i ( i,j )≧ th}   (6)
 
         [0034]    At block  608 , a matching score may be determined based on the template depth values associated with the different regions and the depth values of the selected foreground pixel pixels and the neighboring pixels as associated with the regions using Eqns. (6). In various implementations, block  608  may be undertaken using the following equations: 
         [0000]    
       
         
           
             
               
                 
                   
                       
                   
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         [0000]    Process  600  may then conclude at block  610  where a matching score (H(x,y)) and a sample template radius (Rp) may be provided for the selected foreground pixel  601 . 
         [0035]    Returning to the discussion of  FIG. 2 , having performed template matching at block  206 , process  200  may continue at block  208  with a determination of whether to select additional foreground pixels for processing. For example, process  200  may be undertaken for all foreground pixels in depth image  108 . Thus, if additional foreground pixels remain for processing, then block  208  a may result in a positive determination and process  200  may loop back to undertake blocks  202 - 206  for another foreground pixel. 
         [0036]    If however, block  208  results in a negative determination, process  200  may continue to block  210  where a head location and radius may be identified. In various implementations, block  210  may include comparing all the matching scores (H(x,y)) determined every foreground pixel processed at block  206  and identifying a highest or best matched score having form 
         [0000]        H=max   (x,y)εI,R     p     ε[min.R,max R.] ( H(x,y))   (9)
 
         [0000]    The center of the detected head&#39;s location may then correspond to the location of the foreground pixel having the highest or best matched score, and the associated radius R p  may correspond to the detected head&#39;s radius. 
         [0037]    Process  200  may then conclude at block  212  where values of the head location and radius may be stored. For example, having undertaken blocks  202 - 210 , head detection module  102  may then store the head location and radius values in database  104 . 
         [0038]    In various implementations, process  200  may be performed on a series of foreground pixels by scanning the template across the foreground portions of a depth image. In some implementations, such scanning may include scanning each foreground pixel of an image. In other implementations, such scanning may be undertaken using a sparse grid approach in which only sonic foreground pix are processed. For instance, in various non-limiting examples, only every other foreground pixel, every fifth foreground pixel, every tenth foreground pixel, and so forth may be sampled or processed using process  200 . 
         [0039]    While implementation of example processes  200  and  600 , as illustrated in  FIGS. 2 and 6 , may include the undertaking of all blocks shown in the order illustrated, the present disclosure is not limited in this regard and, in various examples, implementation of processes  200  and  600  may include the undertaking only a subset of all blocks shown and/or in a different order than illustrated. 
         [0040]    In addition any one or more of the processes and/or blocks of  FIGS. 2 and 6  may be undertaken in response to instructions provided by one or more computer program products. Such program products may include signal bearing media providing instructions that, when executed by, for example, one or more processor cores, may provide the functionality described herein. The computer program products may be provided in any form of computer readable medium. Thus, for example, a processor including one or more processor core(s) may undertake one or more of the blocks shown in  FIGS. 2 and 6  in response to instructions conveyed to the processor by a computer readable medium. 
         [0041]      FIG. 7  illustrates an example system  700  in accordance with the present disclosure. System  700  may be used to perform some or all of the various functions discussed herein and may include any device or collection of devices capable of undertaking processes described herein in accordance with various implementations of the present disclosure. For example, system  700  may include selected components of a computing platform or device such as a desktop, mobile or tablet computer, a smart phone, a set top box, etc., although the present disclosure is not limited in this regard. In some implementations, system  700  may be a computing platform or SoC based on Intel® architecture (IA) for CE devices. it will be readily appreciated by one of skill in the art that the implementations described herein can be used with alternative processing systems without departure from the scope of the present disclosure. 
         [0042]    System  700  includes a processor  702  having one or more processor cores  704 . Processor cores  704  may be any type of processor logic capable at least in part of executing software and/or processing data signals. In various examples, processor cores  704  may include CISC processor cores, RISC microprocessor cores, VLIW microprocessor cores, and/or any number of processor cores implementing any combination of instruction sets, or any other processor devices, such as a digital signal processor or microcontroller. 
         [0043]    Processor  702  also includes a decoder  706  that may be used for decoding instructions received by, e.g., a display processor  708  and/or a graphics processor  710 , into control signals and/or microcode entry points. While illustrated in system  700  as components distinct from core(s)  704 , those of skill in the art may recognize that one or more of core(s)  704  may implement decoder  706 , display processor  708  and/or graphics processor  710 . In some implementations, processor  702  may be configured to undertake any of the processes described herein including the example processes described with respect to  FIGS. 2 and 6 . Further, in response to control signals and/or microcode entry points, decoder  706 , display processor  708  and/or graphics processor  710  may perform corresponding operations. 
         [0044]    Processing core(s)  704 , decoder  706 , display processor  708  and/or graphics processor  710  may be communicatively and/or operably coupled through a system interconnect  716  with each other and/or with various other system devices, which may include but are not limited to, for example, a memory controller  714 , an audio controller  718  and/or peripherals  720 . Peripherals  720  may include, for example, a unified serial bus (USB) host port, a Peripheral Component Interconnect (PCI) Express port, a Serial Peripheral Interface (SPI) interface, an expansion bus, and/or other peripherals. While  FIG. 7  illustrates memory controller  714  as being coupled to decoder  706  and the processors  708  and  710  by interconnect  716 , in various implementations, memory controller  714  may be directly coupled to decoder  706 , display processor  708  and/or graphics processor  710 . 
         [0045]    In some implementations, system  700  may communicate with various I/O devices not shown in  FIG. 7  via an I/O bus (also not shown). Such I/O devices may include but are not limited to, for example, a universal asynchronous receiver/transmitter (UART) device, a USB device, an I/O expansion interface or other I/O devices. In various implementations, system  700  may represent at least portions of a system for undertaking mobile, network and/or wireless communications. 
         [0046]    System  900  may further include memory  712 . Memory  712  may be one or more discrete memory components such as a dynamic random access memory (DRAM) device, a static random access memory (SRAM) device, flash memory device, or other memory devices. While  FIG. 7  illustrates memory  712  as being external to processor  702 , in various implementations, memory  712  may be internal to processor  702 . Memory  712  may store instructions and/or data represented by data signals that may be executed by processor  702  in undertaking any of the processes described herein including the example process described with respect to  FIGS. 2 and 6 . For example, memory  712  may store head template depth values, detected head location and radius values and so forth. In some implementations, memory  712  may include a system memory portion and a display memory portion. 
         [0047]    While certain features set forth herein have been described with reference to various implementations, this description is not intended to be construed in a limiting sense. Hence, various modifications of the implementations described herein, as well as other implementations, which are apparent to persons skilled in the art to which the present disclosure pertains are deemed to lie within the spirit and scope of the present disclosure.