基于光流分割在步态识别中的应用

Sun Xiaoying, Zhang Qiuhong, Xu Yanqun
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引用次数: 4

摘要

人体轮廓的质量直接影响步态识别的性能。本文提出了一种鲁棒的步态表示方案,以抑制轮廓不完整对步态的影响。将视频序列中的人体区域划分为若干个子区域,每个子区域用椭圆表示,每个子区域的参数可由光流场中提取的相应运动信息计算得到,从而建立了一种新的人体结构模型——多链接椭圆模型。在识别阶段,最后利用模型参数实现基于动态时间规整技术的步态识别。实验结果证明了该方法具有较高的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of segmentation based on optical flow for gait recognition
The quality of human silhouettes has a direct effect on gait recognition performance. This paper proposes a robust gait representation scheme to suppress the influence of silhouette incompleteness. By means of dividing human body area in a video sequence into several sub-areas, representing each sub-area through an ellipse whose parameters can be calculated from the corresponding motion information extracted from optical flow field, a new body structure model called multi-linked ellipse model is established. In the recognition stage, the parameters of model are finally used to achieve gait recognition based on dynamic time warping technology. Experimental results prove the higher performance of the method.
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