A Gait Classification System using Optical Flow Features

• Published in: Journal of Information Science and Engineering Vol. 30; no. 1; pp. 179 - 193
• Main Authors: 余執彰(Chih-Chang Yu), 鄭建宏(Chien-Hung Cheng), 范國清(Kuo-Chin Fan)
• Format: Journal Article
• Language: English
• Published: Taipei 社團法人中華民國計算語言學學會 01.01.2014; Institute of Information Science, Academia sinica
• Subjects: Algorithms; Applied sciences; Artificial intelligence; Classification; Computer science; control theory; systems; Data processing. List processing. Character string processing; Exact sciences and technology; Feasibility; Feature recognition; Gait; Gaussian; Human; Memory organisation. Data processing; Pattern recognition. Digital image processing. Computational geometry; Recognition; Software; gait classification; optical flow; histogram matching; linear discriminant analysis; principle component analysis; Biometrics; Computer vision; Discriminant analysis; Histogram; Gait; Useful information; Modeling; Posture; Data flow processing; Classification; Gaussian field; Feasibility; Moving body; Optical flow
• ISSN: 1016-2364
• DOI: 10.6688/JISE.2014.30.1.10

Gait classification is an effective and non-intrusive method for human identification. This paper proposes a system to recognize human identity using optical flow features. The distinguishing characteristic of the proposed system is that we only adopt optical flow information and do not consider shape features or other information. The moving object is detected and located from the flow field using a gaussian model. Afterwards, each subject is identified via the established histogram using optical flow features. The proposed system applies and compares three different kinds of optical flow extraction algorithms. Various experiments with two different databases analyzed and discussed the feasibility of the approach. This work demonstrates that optical flow information is useful for gait classification even for unstable optical flows.