[1]WANG Ke-jun,BEN Xian-ye,LIU Li-li.Gait recognition with Radon transform and D principal component analysis[J].CAAI Transactions on Intelligent Systems,2010,5(3):266-271.
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Gait recognition with Radon transform and D principal component analysis

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 3 Page number: 266-271 Column: 学术论文—机器感知与模式识别 Public date: 2010-06-25
Title:
Gait recognition with Radon transform and D principal component analysis
Author(s):
WANG Ke-jun1;  BEN Xian-ye1; 2;  LIU Li-li1; 3
1.College of Automation, Harbin Engineering University, Harbin 150001, China;
2.School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China;
3.CAS Shenyang Institute of Computing Technology Co.〖KG-*1/3〗, Ltd, Shenyang 110171, China
Keywords:
gait recognition;  Radon transform;  two dimensional principal component analysis (2DPCA);  template construction
CLC:
TP391.41
DOI:
-
Abstract:
In the principal component analysis method, concatenating an image matrix often leads to a 1D vector with high dimensionality, which makes it very difficult and timeconsuming to compute the corresponding eigenvectors. By combining static components and dynamic information about the walking style, a novel gait representation was proposed. Gait characteristics were obtained from the Radon transform of gait sequences, where a single image could represent a person’s features by template construction. Then, two dimensional principal component analysis (2DPCA) was used to reduce the dimensions of training and testing data. The nearest neighbor classifier was employed to distinguish the different gaits of human. We tested the proposed gait recognition method on the CASIA gait database. The experimental results demonstrated that, when frequency is chosen properly in template construction, extraction of gait features using the Radon transform and column 2DPCA is very effective. 
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