A set of co-occurrence matrices on the intrinsic manifold of human silhouettes for action recognition

Zheng, Feng, Shao, Ling and Song, Zhan (2010) A set of co-occurrence matrices on the intrinsic manifold of human silhouettes for action recognition. In: CIVR 2010 - ACM International Conference on Image and Video Retrieval, 5th - 7th July 2010, Xi'an, China.

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Abstract

Recognizing actions from a monocular video is a very hot topic in computer vision recently. In this paper, we propose a new representation of actions on the intrinsic shape manifold learned by various graph embedding algorithms. The co-occurrence matrices descriptor captures more temporal information than the histogram descriptor which only considers the spatial information. In addition, we compare the performance of the co-occurrence matrices descriptor on different manifolds learned by various graph embedding methods. The results show that nonlinear algorithms are more robust than linear ones. Furthermore, we conclude that label information plays a critical role in learning more discriminating manifolds.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Action recognition, graph embedding, co-occurrence matrices
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	17 Jun 2015 10:40
Last Modified:	13 Oct 2019 00:31
URI:	http://nrl.northumbria.ac.uk/id/eprint/22985

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