Body Part Detection for Human Pose Estimation and Tracking
Body Part Detection for Human Pose Estimation and Tracking
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DOI：
10.1109/wmvc.2007.10
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发表时间：
2007-02
期刊：
影响因子：
--
通讯作者：
M. Lee;R. Nevatia
中科院分区：
文献类型：
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作者：
M. Lee;R. Nevatia
从单目视频流中准确地跟踪三维人体姿态对于许多应用是重要的。我们描述了一种新的分层方法，用于跟踪人体姿态，使用基于边缘的功能在粗阶段和其他功能的全局优化。首先，通过运动检测人，并通过在图像中拟合椭圆来跟踪人。然后，使用边缘特征找到身体部件，并用于准确地估计身体关节的2D位置。这有助于在最后阶段使用基于采样的搜索方法来引导3D姿态的估计。我们给出了不同真实场景序列的实验结果来说明该方法的性能。
Accurate 3-D human body pose tracking from a monocular video stream is important for a number of applications. We describe a novel hierarchical approach for tracking human pose that uses edge-based features during the coarse stage and later other features for global optimization. At first, humans are detected by motion and tracked by fitting an ellipse in the image. Then, body components are found using edge features and used to estimate the 2D positions of the body joints accurately. This helps to bootstrap the estimation of 3D pose using a sampling-based search method in the last stage. We present experiment results with sequences of different realistic scenes to illustrate the performance of the method.