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Gradient local auto-correlations and extreme learning machine for depth-based activity recognition

  • Chen Chen
  • , Zhenjie Hou*
  • , Baochang Zhang
  • , Junjun Jiang
  • , Yun Yang
  • *此作品的通讯作者
  • University of Texas at Dallas
  • Changzhou University
  • China University of Geosciences, Wuhan
  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper presents a new method for human activity recognition using depth sequences. Each depth sequence is represented by three depth motion maps (DMMs) from three projection views (front, side and top) to capture motion cues. A feature extraction method utilizing spatial and orientational auto-correlations of image local gradients is introduced to extract features from DMMs. The gradient local auto-correlations (GLAC) method employs second order statistics (i.e., auto-correlations) to capture richer information from images than the histogram-based methods (e.g., histogram of oriented gradients) which use first order statistics (i.e., histograms). Based on the extreme learning machine, a fusion framework that incorporates feature-level fusion into decision-level fusion is proposed to effectively combine the GLAC features from DMMs. Experiments on the MSRAction3D and MSRGesture3D datasets demonstrate the effectiveness of the proposed activity recognition algorithm.

源语言英语
主期刊名Advances in Visual Computing - 11th International Symposium, ISVC 2015, Proceedings
编辑Mark Elendt, Richard Boyle, Eric Ragan, Bahram Parvin, Rogerio Feris, Tim McGraw, Ioannis Pavlidis, Regis Kopper, George Bebis, Darko Koracin, Zhao Ye, Gunther Weber
出版商Springer Verlag
613-623
页数11
ISBN(印刷版)9783319278568
DOI
出版状态已出版 - 2015
活动11th International Symposium on Advances in Visual Computing, ISVC 2015 - Las Vegas, 美国
期限: 14 12月 201516 12月 2015

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9474
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议11th International Symposium on Advances in Visual Computing, ISVC 2015
国家/地区美国
Las Vegas
时期14/12/1516/12/15

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