DocumentCode :
3773422
Title :
Gait Recognition Based on Fourier Descriptors and Canonical Time Warping
Author :
Wei Yuan;Qinkun Xiao;Liqin Li
Author_Institution :
Dept. of Electron. Inf. Eng., Xi´an Technol. Univ., Xi´an, China
Volume :
1
fYear :
2015
Firstpage :
64
Lastpage :
67
Abstract :
The Gait recognition includes the 3 main stages: In stage of moving target detection, this paper uses the background subtraction to extract gait silhouette. In stage of feature extraction, using Key frame technology and Fourier descriptors to extract the motion sequence silhouette feature. According to obtain feature data, we can use weighted K-nearest neighbor (KNN) classifier to train gait database and recognize gait sequence with Canonical Time Warping (CTW).
Keywords :
"Feature extraction","Gait recognition","Databases","Classification algorithms","Heuristic algorithms","Hidden Markov models","Training"
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2015 8th International Symposium on
Print_ISBN :
978-1-4673-9586-1
Type :
conf
DOI :
10.1109/ISCID.2015.135
Filename :
7468899
Link To Document :
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