Behavior Recognition of Human Based on Deep Learning

FAN Heng; XU Jun; DENG Yong; XIANG Jinhai

doi:10.13203/j.whugis20140110

Volume 41 Issue 4

Apr. 2016

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Geomatics and Information Science of Wuhan University > 2016 > 41(4): 492-497. > DOI: 10.13203/j.whugis20140110

FAN Heng, XU Jun, DENG Yong, XIANG Jinhai. Behavior Recognition of Human Based on Deep Learning[J]. Geomatics and Information Science of Wuhan University, 2016, 41(4): 492-497. DOI: 10.13203/j.whugis20140110

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Behavior Recognition of Human Based on Deep Learning

1.
College of Engineering, Huazhong Agricultural University, Wuhan 430079, China;
2.
Department of Physics, Center China Normal University, Wuhan 430079, China;
3.
The 722 Research Institute, China Ship Building Industry Corporation, Wuhan 430072, China;
4.
College of Science, Huazhong Agricultural University, Wuhan 430079, China

Funds: The National Natural Science Foundation of China, No.11204099; Fundamental Research Funds for the Central Universities, No.2014BQ083.

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Received Date: June 21, 2014
Published Date: April 04, 2016

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Abstract

To recognize human behaviors in public areas, a new method of recognition was proposed based on deep learning. First, we pre-processed all the images in training and test samples, and utilized GMM to extract moving objects. Then, we built sample sets of various behaviors, and defined different behaviors as priori knowledge to train a deep learning network. Finally, all kinds of behaviors based on the network model of deep learning were recognized. Experimental results demonstrated our method outperforms the existed methods, and the average recognition rate is 96.82%.
- deep learning,
- restricted Boltzmann machine(RBM),
- deep belief networks(DBNs),
- behavior recognition

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