User center-of-mass and mass distribution extraction using depth images
First Claim
1. A method for using a depth image to extract user behavior, comprising:
- receiving a depth image that specifies that a plurality of pixels correspond to a user,wherein the depth image is obtained using a capture device located a distance from the user,wherein the depth image also specifies, for each of the pixels corresponding to the user, a pixel location and a pixel depth, andwherein the pixel depth, specified for each of the pixels corresponding to the user, is indicative of a distance between the capture device and a portion of the user represented by the pixel;
determining, for each of the pixels corresponding to the user, a pixel mass that accounts for a distance between the portion of the user represented by the pixel and the capture device used to obtain the depth image; and
determining, based on the pixel mass determined for each of the pixels corresponding to the user, a depth-based center-of-mass position for the plurality of pixels corresponding to the user that accounts for distances between the portions of the user represented by the pixels and the capture device used to obtain the depth image.
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Abstract
Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. A depth-based center-of-mass position is determined for the plurality of pixels that correspond to the user. Additionally, a depth-based inertia tensor can also be determined for the plurality of pixels that correspond to the user. In certain embodiments, the plurality of pixels that correspond to the user are divided into quadrants and a depth-based quadrant center-of-mass position is determined for each of the quadrants. Additionally, a depth-based quadrant inertia tensor can be determined for each of the quadrants. Based on one or more of the depth-based center-of-mass position, the depth-based inertial tensor, the depth-based quadrant center-of-mass positions or the depth-based quadrant inertia tensors, an application is updated.
217 Citations
19 Claims
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1. A method for using a depth image to extract user behavior, comprising:
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receiving a depth image that specifies that a plurality of pixels correspond to a user, wherein the depth image is obtained using a capture device located a distance from the user, wherein the depth image also specifies, for each of the pixels corresponding to the user, a pixel location and a pixel depth, and wherein the pixel depth, specified for each of the pixels corresponding to the user, is indicative of a distance between the capture device and a portion of the user represented by the pixel; determining, for each of the pixels corresponding to the user, a pixel mass that accounts for a distance between the portion of the user represented by the pixel and the capture device used to obtain the depth image; and determining, based on the pixel mass determined for each of the pixels corresponding to the user, a depth-based center-of-mass position for the plurality of pixels corresponding to the user that accounts for distances between the portions of the user represented by the pixels and the capture device used to obtain the depth image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system that uses depth images to extract user behavior, comprising:
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a capture device that obtains depth images; a communication interface that receives depth images from the capture device; one or more storage devices that store depth images; a display interface; and one or more processors in communication with the one or more storage devices and the display interface, wherein the one or more processors are configured to determine, for each of a plurality of depth images a depth-based center-of-mass position for a plurality of pixels of the depth image that correspond to a user, and a depth-based inertia tensor for the plurality of pixels of the depth image that correspond to the user. - View Dependent Claims (13, 14, 15)
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12. The system of 11, wherein the depth-based center-of mass position and the depth-based inertia tensor are determined in a manner that accounts for distances between portions of the user represented by the pixels and the capture device used to obtain the depth image.
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16. One or more processor readable storage devices having instructions encoded thereon which when executed cause one or more processors to perform a method for using depth images to extract user behavior, the method comprising:
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receiving a depth image that specifies that a plurality of pixels correspond to a user; determining pixel masses for the pixels corresponding to the user; determining, based on the determined pixel masses for the pixels corresponding to the user, a depth-based center-of-mass position for the plurality of pixels corresponding to the user; and determining a depth-based inertia tensor for the plurality of pixels corresponding to the user based on the determined depth-based center-of-mass position for the plurality of pixels corresponding to the user. - View Dependent Claims (17, 18, 19)
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Specification