DocumentCode :
2741941
Title :
Gait Recognition Considering Directions of Walking
Author :
Han, Xu ; Liu, Jiwei ; Li, Lei ; Wang, Zhiliang
Author_Institution :
Inf. & Eng. Sch., Univ. of Sci. & Technol. Beijing
fYear :
2006
fDate :
7-9 June 2006
Firstpage :
1
Lastpage :
5
Abstract :
Studies on gait recognition are mostly based on the assumption that walking direction is parallel to the camera, and the person´s side view is extracted. Walking direction has becoming one of the gait recognition challenge problems. In this paper we explore gait recognition considering any directions of walking which is not definitely parallel to the camera. We propose a novel approach to computing the walking direction and extracting features by employing a human model. Furthermore, a support vector machine (SVM) is performed allowing us to investigate and evaluate the recognition power of any walking directions. We applied our method to the real human walking video data, and achieved high recognition rate. Our approach finds out how changes in walking direction affect gait parameters in terms of recognition performance. As it is entirely based on human gait, our approach is robust to different type of clothes and different walking directions
Keywords :
feature extraction; gait analysis; image motion analysis; support vector machines; feature extraction; gait recognition; projection method; support vector machine; walking direction computation; Cameras; Data mining; Feature extraction; Hidden Markov models; Humans; Legged locomotion; Pattern recognition; Performance evaluation; Support vector machine classification; Support vector machines; Directions of walking; Gait Recognition; Projection Method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cybernetics and Intelligent Systems, 2006 IEEE Conference on
Conference_Location :
Bangkok
Print_ISBN :
1-4244-0023-6
Type :
conf
DOI :
10.1109/ICCIS.2006.252281
Filename :
4017840
Link To Document :
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