A descriptor combining MHI and PCOG for human motion classification

Shao, Ling and Ji, Ling (2010) A descriptor combining MHI and PCOG for human motion classification. In: CIVR 2010 - ACM International Conference on Image and Video Retrieval, 5th - 7th July 2010, Xi'an, China.

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Official URL: http://dx.doi.org/10.1145/1816041.1816077


The performance of human motion classification and recognition systems is highly dependent on the distinctiveness and robustness of the feature descriptor. In this paper, a new descriptor containing motion, shape and spatial layout information is proposed, therefore it is more effective for action modeling and is suitable for detecting and recognizing a variety of actions. Experiments show that the proposed descriptor outperforms other existing methods, such as Moment Invariants and Histogram of Oriented Gradients, on recognizing human motions in an indoor environment with a stationary camera.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Motion Classification, Human Action Recognition, Feature Descriptor, Correlogram, MHI, PCOG
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 17 Jun 2015 10:35
Last Modified: 13 Oct 2019 00:31
URI: http://nrl.northumbria.ac.uk/id/eprint/22984

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