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Sensors 2015, 15(1), 932-964; doi:10.3390/s150100932

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.
Received: 19 September 2014 / Accepted: 23 December 2014 / Published: 7 January 2015
(This article belongs to the Section Physical Sensors)

Abstract

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
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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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.

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