A hierarchical human activity recognition framework based on automated reasoning

Chen, Shuwei and Liu, Jun and Wang, Hui and Augusto, Juan Carlos (2013) A hierarchical human activity recognition framework based on automated reasoning. In: IEEE International Conference on Systems, Man and Cybernetics (SMC2013), 13-16 October, 2013, Manchester, UK.

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Abstract

Conventional human activity recognition approaches are mainly based on machine learning methods, which are not working well for composite activity recognition due to the complexity and uncertainty of real scenarios. We propose in this paper an automated reasoning based hierarchical framework for human activity recognition. This approach constructs a hierarchical structure for representing the composite activity by a composition of lower-level actions and gestures according to its semantic meaning. This hierarchical structure is then transformed into logical formulas and rules, based on which the resolution based automated reasoning is applied to recognize the composite activity given the recognized lower-level actions by machine learning methods.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science > Intelligent Environments group
A. > School of Science and Technology > Computer Science
Item ID: 13006
Useful Links:
Depositing User: Juan Augusto
Date Deposited: 10 Feb 2014 06:39
Last Modified: 13 Oct 2016 14:30
URI: http://eprints.mdx.ac.uk/id/eprint/13006

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