一种基于光流的多区域分割在步态识别中的应用

摘要

The quality of human silhouettes has a direct effect on gait recognition performance. This paper proposed 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 and representing each sub-area by 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 was established. In the recognition stage, the parameters of model are finally used to a-chieve gait recognition based on dynamic time warping technology. Experimental results prove the higher performance of the method.%人体目标分割的质量对步态识别的性能有直接的影响.提出了一种鲁棒性的步态表示方法,即利用光流特征提取视频中的运动信息,并将目标人体区域部分按人体结构特点划分为多个子区域,每个子区域通过基于光流特征的椭圆模型进行拟合,建立多区域椭圆模型的人体结构模型.识别过程中将模型参数作为步态特征,结合动态时间规整技术解决了动态模式的相似度量和匹配问题.实验表明,该算法可以有效地提高识别算法的鲁棒性,并且具有较好的识别性能.