Systems and methods for human body pose estimation
First Claim
1. A computer-implemented method for use in body pose estimation, comprising:
- (a) obtaining training data that includes observation vector data and corresponding pose vector data for a plurality of images,wherein the observation vector data is representative of the images in observation space, and the pose vector data is representative of the same images in pose space; and
(b) computing, based on the training data, a model that includes parameters of mapping from the observation space to latent space, parameters of mapping from the latent space to the pose space, and parameters of the latent space;
wherein the latent space has a lower dimensionality than the observation space, andwherein the latent space has a lower dimensionality than the pose space.
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Abstract
Systems and computer-implemented methods for use in body pose estimation are provided. Training data is obtained, where the training data includes observation vector data and corresponding pose vector data for a plurality of images. The observation vector data is representative of the images in observation space. The pose vector data is representative of the same images in pose space. Based on the training data, a model is computed that includes parameters of mapping from the observation space to latent space, parameters of mapping from the latent space to the pose space, and parameters of the latent space. The latent space has a lower dimensionality than the observation space and the pose space.
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Citations
22 Claims
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1. A computer-implemented method for use in body pose estimation, comprising:
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(a) obtaining training data that includes observation vector data and corresponding pose vector data for a plurality of images, wherein the observation vector data is representative of the images in observation space, and the pose vector data is representative of the same images in pose space; and (b) computing, based on the training data, a model that includes parameters of mapping from the observation space to latent space, parameters of mapping from the latent space to the pose space, and parameters of the latent space; wherein the latent space has a lower dimensionality than the observation space, and wherein the latent space has a lower dimensionality than the pose space. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A system for use in body pose estimation, comprising:
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an input module configured to obtain training data that includes observation vector data and corresponding pose vector data for a plurality of images, wherein the observation vector data is representative of the images in observation space, and the pose vector data is representative of the same images in pose space; and one or more processor configured to compute, based on the training data, a model that includes parameters of mapping from the observation space to latent space, parameters of mapping from the latent space to the pose space, and parameters of the latent space; wherein the latent space has a lower dimensionality than the observation space, and wherein the latent space has a lower dimensionality than the pose space. - View Dependent Claims (18, 19)
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20. A computer program product, comprising a non-transitory computer-readable medium having computer program instructions embodied thereon to cause one or more processor to implement a method for use in body pose estimation, the method comprising:
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obtaining training data that includes observation vector data and corresponding pose vector data for a plurality of images, wherein the observation vector data is representative of the images in observation space, and the pose vector data is representative of the same images in pose space; and computing, based on the training data, a model that includes parameters of mapping from the observation space to latent space, parameters of mapping from the latent space to the pose space, and parameters of the latent space; wherein the latent space has a lower dimensionality than the observation space, and wherein the latent space has a lower dimensionality than the pose space. - View Dependent Claims (21, 22)
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Specification