Informative joints based human action recognition using skeleton contexts-Reference-Cited by-同舟云学术

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Informative joints based human action recognition using skeleton contexts

Published:2015-04 Issue: Volume:33 Page:29-40
ISSN:0923-5965
Container-title:Signal Processing: Image Communication
language:en
Short-container-title:Signal Processing: Image Communication

Author:

Jiang Min,Kong Jun,Bebis George,Huo Hongtao

Funder

National Natural Science Foundation of China

Xinjiang Uygur Autonomous Regions Natural Science Foundation

Technology Research Project of the Ministry of Public Security of China

Xinjiang Uygur Autonomous Regions University Scientific Research Key Project

111 Project

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference29 articles.

1. A. Gaidon, Z. Harchaoui, C. Schmid, Actom sequence models for efficient action detection, in: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011, pp. 3201–3208.

2. Motion history image;Ahad;Mach. Vis. Appl.,2012

3. Canonical correlation analysis of video volume tensors for action categorization and detection;Kim;IEEE Trans. Pattern Anal. Mach. Intell.,2009

4. C. Schuldt, I. Laptev, B. Caputo, Recognizing human actions: a local SVM approach, in: Proceedings of the 17th International Conference on Pattern Recognition (ICPR), vol. 3, 2004, pp. 32–36.

5. M. Marszalek, I. Laptev, C. Schmid, Actions in context, in: 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2009, pp. 2929–2936.

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