Gait Recognition Based on Key Frame and Elliptical Model

摘要：

In this paper, a robust gait recognition algorithm based on key frame and ellipse model is proposed, which solves the problems including finding key frames on discontinuous contour segmentation and accurate feature extraction on ellipse model. Firstly, a robust extraction algorithm of key fame is introduced, which makes detection of key fames easier and more accurate. Secondly, human bodies corresponding to nearest and furthest distance between two legs in the key frame are separately divided into four parts composed of head, torso, and lower limb above knee and under knee, and six parts consisting of head, torso, left and right calves, and left and right thighs. These parts are fitted to corresponding ellipse parameters by the new fitting algorithm. Thirdly, an improved algorithm based on ellipse fitting is proposed in the paper, which calculates accurate ellipse parameters as human feature. Lastly, according to accurate parameters on ellipses, Euclidean and Mahalanobis distances are used to judge human identification. Experimental results show that recognition algorithm is effective.

关键词： Gait recognition Key frame extraction Ellipse fitting UCSD database

作者: Junhong Xu Wang Cong Jin Li Lei Wang Lijie Li Hong Liang

作者单位: Automation College,Harbin Engineering University Harbin,Heilongjiang Province,150001,China Departmen Automation College,Harbin Engineering University Harbin,Heilongjiang Province,150001,China Departmen

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）