3D gait recognition using multiple cameras
3D gait recognition using multiple cameras
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DOI：
10.1109/fgr.2006.2
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发表时间：
2006-04
期刊：
影响因子：
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通讯作者：
Guoying Zhao;Guoyi Liu;Hua Li;M. Pietikäinen
中科院分区：
文献类型：
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作者：
Guoying Zhao;Guoyi Liu;Hua Li;M. Pietikäinen
步态识别用于根据步态识别图像序列中的个体。几乎所有的步态识别方法都是基于分析单个摄像机拍摄的图像序列的2D方法。本文以多个摄像机采集的视频序列为输入，建立人体三维模型。通过应用局部优化算法来跟踪运动。提取关键节段的长度作为静态参数，将肢体运动轨迹作为动态特征。最后利用线性时间归一化方法进行匹配和识别。提出的基于三维跟踪与识别的方法对视点变化具有较强的鲁棒性。此外，对于含有复杂曲面变化的序列，我们得到了比2D方法更好的结果，这证明了该算法的有效性
Gait recognition is used to identify individuals in image sequences by the way they walk. Nearly all of the approaches proposed for gait recognition are 2D methods based on analyzing image sequences captured by a single camera. In this paper, video sequences captured by multiple cameras are used as input, and then a human 3D model is set up. The motion is tracked by applying a local optimization algorithm. The lengths of key segments are extracted as static parameters, and the motion trajectories of lower limbs are used as dynamic features. Finally, linear time normalization is exploited for matching and recognition. The proposed method based on 3D tracking and recognition is robust to the changes of viewpoints. Moreover, better results are achieved for sequences containing difficult surface variations than with 2D methods, which prove the efficiency of our algorithm