3-Dimensional motion recognition by 4-dimensional Higher-Order Local Auto-Correlation

Hiroki Mori, Takaomi Kanda, Dai Hirose, Minoru Asada

研究成果: Conference contribution

抄録

In this paper, we propose a 4-Dimensional Higher-order Local Auto-Correlation (4D HLAC). The method aims to extract the features of a 3D time series, which is regarded as a 4D static pattern. This is an orthodox extension of the original HLAC, which represents correlations among local values in 2D images and can effectively summarize motion in 3D space. To recognize motion in the real world, a recognition system should exploit motion information from the real-world structure. The 4D HLAC feature vector is expected to capture representations for general 3D motion recognition, because the original HLAC performed very well in image recognition tasks. Based on experimental results showing high recognition performance and low computational cost, we conclude that our method has a strong advantage for 3D time series recognition, even in practical situations.

本文言語English
ホスト出版物のタイトルICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings
編集者Maria De Marsico, Ana Fred, Mario Figueiredo
出版社SciTePress
ページ223-231
ページ数9
ISBN(電子版)9789897580765
出版ステータスPublished - 2015
外部発表はい
イベント4th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2015 - Lisbon, Portugal
継続期間: 2015 1 102015 1 12

出版物シリーズ

名前ICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings
1

Other

Other4th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2015
国/地域Portugal
CityLisbon
Period15/1/1015/1/12

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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