Controlled human pose estimation from depth image streams
First Claim
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1. A computer based method for estimating a pose of a human subject, the method comprising:
- receiving an image of the human subject;
detecting a plurality of detected features of the human subject on the image, the detected features comprising representations of anatomical body parts on the human subject;
determining that at least one undetected feature is missing or occluded based on the detected features;
augmenting the detected features with at least one predicted feature to replace the at least one undetected feature, the at least one predicted feature generated using a previous pose estimated using a posture model and a previously received image; and
estimating a pose of the human subject using the posture model, the posture model estimating the pose using the detected features, the at least one predicted feature, and a plurality of kinematic constraints, the posture model using an inverse kinematic computation configured to, for each of the expected features;
reduce an error between the expected feature and a corresponding one of the detected features,except that for the at least one undetected feature, instead reducing an error between the expected feature and the at least one corresponding predicted feature.
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Abstract
A system, method, and computer program product for estimating upper body human pose are described. According to one aspect, a plurality of anatomical features are detected in a depth image of the human actor. The method detects a head, neck, and torso (H-N-T) template in the depth image, and detects the features in the depth image based on the H-N-T template. An estimated pose of a human model is estimated based on the detected features and kinematic constraints of the human model.
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22 Claims
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1. A computer based method for estimating a pose of a human subject, the method comprising:
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receiving an image of the human subject; detecting a plurality of detected features of the human subject on the image, the detected features comprising representations of anatomical body parts on the human subject; determining that at least one undetected feature is missing or occluded based on the detected features; augmenting the detected features with at least one predicted feature to replace the at least one undetected feature, the at least one predicted feature generated using a previous pose estimated using a posture model and a previously received image; and estimating a pose of the human subject using the posture model, the posture model estimating the pose using the detected features, the at least one predicted feature, and a plurality of kinematic constraints, the posture model using an inverse kinematic computation configured to, for each of the expected features; reduce an error between the expected feature and a corresponding one of the detected features, except that for the at least one undetected feature, instead reducing an error between the expected feature and the at least one corresponding predicted feature. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 21, 22)
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12. A computer program product for estimating a pose of a human subject, the computer program product comprising a non-transitory computer-readable storage medium containing executable computer program code for performing a method comprising:
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receiving an image of the human subject; detecting a plurality of detected features of the human subject on the image, the detected features comprising representations of anatomical body parts on the human subject; determining that at least one undetected feature is missing or occluded based on the detected features; augmenting the detected features with at least one predicted feature to replace the at least one undetected feature, the at least one predicted feature generated using a previous pose estimated using a posture model and a previously received image; and estimating a pose of the human subject using the posture model, the posture model estimating the pose using the detected features, the at least one predicted feature, and a plurality of kinematic constraints, the posture model using an inverse kinematic computation configured to, for each of the expected features; reduce an error between the expected feature and a corresponding one of the detected features, except that for the at least one undetected feature, instead reducing an error between the expected feature and the at least one corresponding predicted feature. - View Dependent Claims (13, 14, 15, 16)
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17. A system for estimating a pose of a human subject, the system comprising:
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a computer processor for executing executable computer program code; a computer-readable storage medium containing the executable computer program code for performing a method comprising; receiving an image of the human subject; detecting a plurality of detected features of the human subject on the image, the detected features comprising representations of anatomical body parts on the human subject; determining that at least one undetected feature is missing or occluded based on the detected features; augmenting the detected features with at least one predicted feature to replace the at least one undetected feature, the at least one predicted feature generated using a previous pose estimated using a posture model and a previously received image; and estimating a pose of the human subject using the posture model, the posture model estimating the pose using the detected features, the at least one predicted feature, and a plurality of kinematic constraints, the posture model using an inverse kinematic computation configured to for each of the expected features; reduce an error between the expected feature and a corresponding one of the detected features, except that for the at least one undetected feature, instead reducing an error between the expected feature and the at least one corresponding predicted feature. - View Dependent Claims (18, 19, 20)
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Specification