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Fast Human Pose Estimation Using Appearance And Motion Via Multi-Dimensional Boosting Regression
Fast Human Pose Estimation Using Appearance And Motion Via Multi-Dimensional Boosting Regression
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机译:通过外观和运动通过多维Boosting回归进行快速人体姿态估计
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摘要
Methods and systems are described for three-dimensional pose estimation. A training module determines a mapping function between a training image sequence and pose representations of a subject in the training image sequence. The training image sequence is represented by a set of appearance and motion patches. A set of filters are applied to the appearance and motion patches to extract features of the training images. Based on the extracted features, the training module learns a multidimensional mapping function that maps the motion and appearance patches to the pose representations of the subject. A testing module outputs a fast human pose estimation by applying the learned mapping function to a test image sequence.
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