Evaluation of Genetic Programs in Multiple Cases for Gait Classification and Recognition

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2016/09/01

タイトル(英語): Evaluation of Genetic Programs in Multiple Cases for Gait Classification and Recognition

著者名: Dipak Gaire Sharma (Graduate School of Science and Engineering, Doshisha University), Rahadian Yusuf (Graduate School of Science and Engineering, Doshisha University), Ivan Tanev (Graduate School of Science and Engineering, Doshisha University), Katsunori

著者名(英語): Dipak Gaire Sharma (Graduate School of Science and Engineering, Doshisha University), Rahadian Yusuf (Graduate School of Science and Engineering, Doshisha University), Ivan Tanev (Graduate School of Science and Engineering, Doshisha University), Katsunori Shimohara (Graduate School of Science and Engineering, Doshisha University)

キーワード: Biometrics，Gait Classification，Genetic Programming，Human Gait，Human Recognition

要約(英語): The analysis of human motion is a challenging research domain that attracts the attention of researchers from several disciplines, including sociopsychology, neurobiology, and computer science. A successful recognition of the person's walk could be used for personal identification, and also, would be important for understanding the human's emotions, personality, and neurological disorders. However, recognizing the human gaits is a challenging task because of the complexity of the eventual analytical model that defines the numerical relationship between the relevant features of the gait. In our previous work we proposed an approach of applying genetic programming to automatically design such a model in a way much similar to the evolution in nature. In this paper, we continue the focus on human gait recognition, and present an analysis of the trade-off between the evolution of genetic programs (GPs) and their performance. We consider different training cases, provided that the computational resources and other parameters are kept constant. Furthermore, in our previous work, there was an important unanswered question regarding the effect of the increased number of fitness cases and the use of experts in collaborative filtering on the evolution of GPs and gait recognition. This study is an attempt to explore the same unexplained question.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.136 No.9 （2016） 特集：神経工学・サイバネティックス・生体工学

本誌掲載ページ: 1400-1410 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/136/9/136_1400/_article/-char/ja/