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Compositional interaction descriptor for human interaction recognition
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DOI：10.1016/j.neucom.2017.06.009.png)
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Abstract
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In this paper, we address the problem of human interaction recognition. We propose a novel compositional interaction descriptor to represent complex human interactions containing high intra and inter-class variations. The compositional interaction descriptor represents motion relationships on individual, local, and global levels to build a highly discriminative description. We evaluate the proposed method using UT-Interaction and BIT-Interaction public benchmark datasets. Experimental results demonstrate that the performance of the proposed approach is on a par with previous methods. (C) 2017 Elsevier B.V. All rights reserved.
Keywords:
Human interaction recognition
Compositional interaction descriptor
Human motion analysis
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