Behavior recognition of human based on deep learning

被引：0

作者：

Fan H. ^{[1
]}

Xu J. ^{[2
]}

Deng Y. ^{[3
]}

Xiang J. ^{[4
]}

机构：

[1] College of Engineering, Huazhong Agricultural University, Wuhan

[2] Department of Physics, Center China Normal University, Wuhan

[3] The 722 Research Institute, China Ship Building Industry Corporation, Wuhan

[4] College of Science, Huazhong Agricultural University, Wuhan

来源：

Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2016年 / 41卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Behavior recognition; Deep belief networks (DBNs); Deep learning; Restricted Boltzmann machine (RBM);

D O I：

10.13203/j.whugis20140110

中图分类号：

学科分类号：

摘要：

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%. © 2016, Wuhan University All right reserved.

引用

页码：492 / 497

页数：5

共 23 条

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