Action recognition using Correlogram of Body Poses and spectral regression

Shao, Ling, Wu, Di and Chen, Xiuli (2011) Action recognition using Correlogram of Body Poses and spectral regression. In: ICIP 2011 - 18th IEEE International Conference on Image Processing, 11th - 14th September 2011, Brussels, Belgium.

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Human action recognition is an important topic in computer vision with its applications in robotics, video surveillance, human-computer interaction, user interface design, and multimedia video retrieval, etc. In this paper, we propose a novel representation for human actions using Correlogram of Body Poses (CBP) which takes advantage of both the probabilistic distribution and the temporal relationship of human poses. To reduce the high dimensionality of the CBP representation, an efficient subspace learning technique called Spectral Regression Discriminant Analysis (SRDA) is explored. Experimental results on the challenging IXMAS dataset show that the proposed algorithm outperforms the state-of-the-art methods on action recognition.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Action Recognition, Correlogram of Body Poses (CBP), Histogram of Body Poses (HBP), Spectral Regression Discriminant Analysis (SRDA)
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 16 Jun 2015 14:45
Last Modified: 13 Oct 2019 00:31

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