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Faculty of Engineering, Kyushu Institute of Technology
Graduate School of Engineering, Kyushu Institute of Technology
Graduate School of Engineering, Kyushu Institute of Technology
Graduate School of Engineering, Kyushu Institute of Technology
抄録
This paper proposes a new method of describing a self-occlusive human motion, particularly in the depth direction, which has been considered little in the motion/action recognition studies to date in spite of its importance in our daily life. A Motion History Image (MHI) is a well-known method of describing a motion by a single gray value image, but it suffers from a self-occlusion problem in which present motion overwrites past motion. To solve this difficulty, a Reverse description MHI (RMHI) is proposed in the paper. RMHI and the original MHI are both employed for motion representation in the proposed method; the former for approach motion, whereas the latter for leave motion. In the experiment on motion recognition, motions are described by RMHI or MHI according to motion direction, transformed then to Hu moment vectors, and finally recognized employing the k-nearest neighbor. Experimental results show effectiveness of the RMHI description.
雑誌名
International Journal of Biomedical Soft Computing and Human Sciences
巻
24
号
1
ページ
1 - 7
発行年
2019-07
出版者
バイオメディカル・ファジィ・システム学会
ISSN
2185-2421
書誌レコードID
AA11451470
DOI
https://doi.org/10.24466/ijbschs.24.1_1
権利
Copyright (c) 2019 Biomedical Fuzzy Systems Association