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Journal of Zhejiang University SCIENCE C 1998 Vol.-1 No.-1 P.

http://doi.org/10.1631/FITEE.2000377


A partition approach for robust gait recognition based on gait template fusion


Author(s):  Ke-jun WANG, Liang-liang LIU, Xin-nan DING, Kai-qiang YU, Gang HU

Affiliation(s):  College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China

Corresponding email(s):   heukejun@126.com, liuliangliang@hrbeu.edu.cn, dingxinnan@hrbeu.edu.cn, yukaiqiang@hrbeu.edu.cn, hugang@hrbeu.edu.cn

Key Words:  Gait recognition, Partitioning algorithms, Gait templates, Gait analysis, Gait energy image, Deep convolutional neural networks, Biometrics recognition, Pattern recognition


Ke-jun WANG, Liang-liang LIU, Xin-nan DING, Kai-qiang YU, Gang HU. A partition approach for robust gait recognition based on gait template fusion[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .

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Abstract: 
gait recognition has significant potential for remote human identification, but it is easily influenced by identity-unrelated factors such as clothing worn, carrying an object, and views. Many gait templates have been presented that can effectively represent gait features. Each gait template has its advantages and different prominent information. In this paper, gait template fusion is proposed to improve the classical representative gait template (such as a gait energy image), which represents incomplete information that is sensitive to changes in contour, and the fused template. We also present a partitioning method to reflect the different gait habits of different body parts of each pedestrian. The fused template is cropped into three parts (head, trunk, and leg regions) depending on the human body, and the three parts are then sent into the convolutional neural network to learn merged features. We present an extensive empirical evaluation of the CASIA-B dataset and compare it with existing works. The results show good accuracy and robustness of the proposed method for gait recognition.

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