用行人轮廓的分布直方图分类和识别步态  

Gait Recognition Using Distributions of Silhouette Feature

作　　者：陈实[1,2] 马天骏[2] 高有行[2] 

机构地区：[1]浙江万里学院设计学院,浙江宁波315100 [2]西安电子科技大学计算机学院,西安710071

出　　处：《计算机研究与发展》2009年第2期295-301,共7页Journal of Computer Research and Development

基　　金：宁波市自然科学基金项目(2008A610011);陕西省自然科学基金项目(2006F48)~~

摘　　要：现有的步态识别方法对行人轮廓匹配的鲁棒性差,识别率不高.提出了一种基于轮廓直方图分布的行人步态识别方法.首先提取行人二值轮廓序列;然后通过人体局部轮廓的点分布直方图获取步态周期;继而构造表达帧间关系的周期步态平面,设计一种直方图分布的描述子获得帧姿态特征值,计算出姿态轮廓特征分布间的Jeffery距离,结合动态时间规整技术获取了测试序列和参考序列间的匹配相似度,最终完成了识别.在Soton步态数据库上进行了实验,提出算法的正确识别率可达87.59%,与相关文献的对比分析表明算法是有效的.Vision-based human identification at a distance in surveillance has recently gained more attentions. Gait has the advantages of being non-invasive and difficult to conceal, and is also the only perceivable biometric at a distance. This paper introduces a novel feature representation method for gait analysis and recognition applications. The method includes following steps： first, silhouette extraction is performed for each image sequence. Secondly, the distributions of sampled points from the human local silhouette are analyzed and the gait cycle is detected by a histogram-based approach. Thirdly, by tiling and dispersing all image frames across one gait cycle in a two-dimensional plane along a ring frame by frame at a fixed interval, a contextual stances appearance model is built. The gait appearance model consists of the structural information of the individual silhouette and contextual silhouettes centered at the current frame in the polar-plane. With a designed invariant histogram-based descriptor, the gait appearance characteristics are described as a sequence of shape distributions. These distributions are finally used to achieve gait recognition based on Jeffrey divergence matching criterion and dynamic time warping technology. Recognition capability is illustrated by an 87. 59% CCR on Soton database and the result shows that our approach outperforms existing methods.

关 键 词：步态识别 行为特征 步态分析 行人轮廓 形状匹配 直方图分布 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]