一种基于时空分析的步态识别方法

A Method for Human Gait Recognition Using Spatial-Temporal Analysis

提出一种基于侧影的非模型步态识别方法,从图像序列中提取特征进行识别.首先,采用背景减除技术检测跟踪人的侧影,提取出相应的侧影形状轮廓.然后,用新的轮廓形状描述和分析方法对轮廓形状进行时空分析,并运用离散傅立叶变换进一步提取最终用于识别的步态特征.该描述和分析方法兼顾步态的空间和时间信息,能在较低的代价下表达步态运动的时空变化模式.最后,运用标准的模式分类器对步态序列进行训练和识别.在常用数据库上所做测试的结果表明,本方法行之有效.

A new method for model-free recognition of gait based on silhouette in computer vision sequences is proposed. The silhouette shape is represented by a novel approach which includes not only the spatial body contour but also the temporal information. Using this shape representation, the temporal information is extracted with low cost of computation. First, a background subtraction is used to separate objects from background, and gait cycle is obtained by analyzing the variety of the silhouette width and height. Then, the spatial shape of walker and their motion by the temporal matrix are presented, and Discrete Fourier analysis is used to analyze the gait feature. The nearest neighbor classifier is used to distinguish the different gaits of human. The performance of the proposed approach is tested on different gait databases. Recognition results show it is efficient.