首页> 外文会议>International Workshop on Intelligent Computing in Pattern Analysis/Synthesis(IWICPAS 2006); 20060826-27; Xi'an(CN) >Human Pose Estimation from Polluted Silhouettes Using Sub-manifold Voting Strategy
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Human Pose Estimation from Polluted Silhouettes Using Sub-manifold Voting Strategy

机译:基于子流形投票策略的污染轮廓人体姿态估计

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In this paper, we introduce a framework of human pose estimation from polluted silhouettes due to occlusions or shadows. Since the body pose (and configuration) can be estimated by partial components of the silhouette, a robust statistical method is applied to extract useful information from these components. In this method a Gaussian Process model is used to create each sub-manifold corresponding to the component of input data in advance. A sub-manifold voting strategy is then applied to infer the pose structure based on these sub-manifolds. Experiments show that our approach has a great ability to estimate human poses from polluted silhouettes with small computational burden.
机译:在本文中,我们介绍了一种根据遮挡或阴影污染轮廓来估计人体姿势的框架。由于可以通过轮廓的部分分量来估计身体姿势(和构型),因此采用了一种可靠的统计方法来从这些分量中提取有用的信息。在这种方法中,使用高斯过程模型预先创建与输入数据的分量相对应的每个子流形。然后应用子流形投票策略基于这些子流形来推断姿势结构。实验表明,我们的方法具有从污染的轮廓估计人体姿势的强大能力,而计算负担却很小。

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