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Predicting subject body poses and subject movement intent using probabilistic generative models
Predicting subject body poses and subject movement intent using probabilistic generative models
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机译:预测主体主体使用概率生成模型的姿势和主题运动意图
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摘要
Certain aspects of the present disclosure are directed to methods and apparatus for predicting subject motion using probabilistic models. One example method generally includes receiving training data comprising a set of subject pose trees. The set of subject pose trees comprises a plurality of subsets of subject pose trees associated with an image in a sequence of images, and each subject pose tree in the subset indicates a location along an axis of the image at which each of a plurality of joints of a subject is located. The received training data may be processed in a convolutional neural network to generate a trained probabilistic model for predicting joint distribution and subject motion based on density estimation. The trained probabilistic model may be deployed to a computer vision system and configured to generate a probability distribution for the location of each joint along the axis.
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