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Human Activities Recognition Based on Skeleton Information via Sparse Representation
Liu, Suolan,Kong, Lizhi,Wang, Hongyuan Korean Institute of Information Scientists and Eng 2018 Journal of Computing Science and Engineering Vol.12 No.1
Human activities recognition is a challenging task due to its complexity of human movements and the variety performed by different subjects for the same action. This paper presents a recognition algorithm by using skeleton information generated from depth maps. Concatenating motion features and temporal constraint feature produces feature vector. Reducing dictionary scale proposes an improved fast classifier based on sparse representation. The developed method is shown to be effective by recognizing different activities on the UTD-MHAD dataset. Comparison results indicate superior performance of our method over some existing methods.
Human Activities Recognition Based on Skeleton Information via Sparse Representation
Suolan Liu,Lizhi Kong,Hongyuan Wang 한국정보과학회 2018 Journal of Computing Science and Engineering Vol.12 No.1
Human activities recognition is a challenging task due to its complexity of human movements and the variety performed by different subjects for the same action. This paper presents a recognition algorithm by using skeleton information generated from depth maps. Concatenating motion features and temporal constraint feature produces feature vector. Reducing dictionary scale proposes an improved fast classifier based on sparse representation. The developed method is shown to be effective by recognizing different activities on the UTD-MHAD dataset. Comparison results indicate superior performance of our method over some existing methods.