title: Class Energy Image analysis for video sensor-based gait recognition: a review.
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.
authors.affiliation: College of Automation, Harbin Engineering University, Harbin 150001, China. lvlewen1988@163.com.
authors.forename: Zhuowen
authors.initials: Z
authors.lastname: Lv
authors.affiliation: College of Automation, Harbin Engineering University, Harbin 150001, China. xingxl@hrbeu.edu.cn.
authors.forename: Xianglei
authors.initials: X
authors.lastname: Xing
authors.affiliation: College of Automation, Harbin Engineering University, Harbin 150001, China. wangkejun@hrbeu.edu.cn.
authors.forename: Kejun
authors.initials: K
authors.lastname: Wang
authors.affiliation: Department of Computer Engineering, Kyung Hee University, Seoul 130-701, Korea. donghai@oslab.khu.ac.kr.
authors.forename: Donghai
authors.initials: D
authors.lastname: Guan
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000295:instrumentation*; D005684:Gait / Q000502:physiology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D010363:Pattern Recognition, Automated; D014741:Video Recording