A gait classification system using optical flow features

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Title:	A gait classification system using optical flow features
Authors:	范國清;Yu), 余執彰(Chih-Chang;Cheng), 鄭建宏(Chien-Hung;Fan), 范國清(Kuo-Chin
Contributors:	資訊電機學院資訊工程學系
Keywords:	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
Date:	2014-01-01
Issue Date:	2026-04-23 13:03:21 (UTC+8)
Publisher:	Institute of Information Science;Taipei: 社團法人中華民國計算語言學學會
Abstract:	摘要： 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. 出版者： Taipei: 社團法人中華民國計算語言學學會出版日期： 2014-01-01 出處： Journal of Information Science and Engineering, 2014-01, Vol.30 (1), p.179-193 資源來源：華藝CEPS中文電子期刊服務版權： 2015 INIST-CNRS 識別號： ISSN: 1016-2364 識別號： DOI: 10.6688/JISE.2014.30.1.10
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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