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Review

Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review

1
College of Automation, Harbin Engineering University, Harbin 150001, China
2
Department of Computer Engineering, Kyung Hee University, Seoul 130-701, Korea
*
Authors to whom correspondence should be addressed.
Sensors 2015, 15(1), 932-964; https://doi.org/10.3390/s150100932
Received: 19 September 2014 / Accepted: 23 December 2014 / Published: 7 January 2015
(This article belongs to the Section Physical Sensors)
Gait is a unique perceptible biometric feature at larger distances, and the gait representation approach plays a key role in a video sensor-based gait recognition system. Class Energy Image is one of the most important gait representation methods based on appearance, which has received lots of attentions. In this paper, we reviewed the expressions and meanings of various Class Energy Image approaches, and analyzed the information in the Class Energy Images. Furthermore, the effectiveness and robustness of these approaches were compared on the benchmark gait databases. We outlined the research challenges and provided promising future directions for the field. To the best of our knowledge, this is the first review that focuses on Class Energy Image. It can provide a useful reference in the literature of video sensor-based gait representation approach. View Full-Text
Keywords: gait recognition; gait representation; Class Energy Image gait recognition; gait representation; Class Energy Image
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MDPI and ACS Style

Lv, Z.; Xing, X.; Wang, K.; Guan, D. Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review. Sensors 2015, 15, 932-964. https://doi.org/10.3390/s150100932

AMA Style

Lv Z, Xing X, Wang K, Guan D. Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review. Sensors. 2015; 15(1):932-964. https://doi.org/10.3390/s150100932

Chicago/Turabian Style

Lv, Zhuowen, Xianglei Xing, Kejun Wang, and Donghai Guan. 2015. "Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review" Sensors 15, no. 1: 932-964. https://doi.org/10.3390/s150100932

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