View-based Human Motion Recognition in the Presence of Outliers
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概要
- 論文の詳細を見る
In this paper, we present a view-based human motion recognition method, which has been found robust against outliers. The basic motion history image (MHI) has been updated considering multi-dimensional history and energy images to calculate the feature vectors for recognizing various complex human motions. We recognized various actions of the 'rajio-taiso' (i.e., Japanese Radio Physical Exercise) by employing this developed method. This exercise was conducted by some non-professionals and therefore, the input video data has lots of disarray and variations along with the complex movements of the exercise. Moreover, some movement contains outliers and noises. We found better recognition rate compare to motion history image method.
- バイオメディカル・ファジィ・システム学会の論文
著者
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Ishikawa S.
Department of Electrical and Electronic Engineering, Faculty of Engineering, Oita University
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Ahad Md.
Department Of Control Engineering Kyushu Institute Of Technology
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OGATA T.
Department of Control Engineering, Kyushu Institute of Technology
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TAN J.K.
Department of Control Engineering, Kyushu Institute of Technology
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KIM H.S.
Department of Control Engineering, Kyushu Institute of Technology
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Tan J.k.
Department Of Control Engineering Kyushu Institute Of Technology
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Kim H.s.
Department Of Control Engineering Kyushu Institute Of Technology
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Ishikawa S.
Department of Biology, Faculty of Science, Kumamoto University
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