Gait recognition based on Fourier descriptors and Canonical Time Warping

被引：6
|
作者：
Yuan, Wei [1 ]
Xiao, Qinkun [1 ]
Li, Liqin [1 ]
机构：
[1] Xian Technol Univ, Dept Elect Informat Engn, Xian, Peoples R China
来源：
2015 8TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1 | 2015年
关键词：
Fourier descriptors; Weighted K-nearest neighbor; CTW Matching; Gaussian mixture background modeling;
D O I：
10.1109/ISCID.2015.135
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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).
引用
收藏
页码：64 / 67
页数：4
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