吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (增刊1): 489-492.

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Biomimetic recognition method of human behavior based on HOG and SVM

WANG Dan1, ZHANG Xiang-he2   

  1. 1. Editorial Department of Journal of Bionic Engineering, Jilin University, Changchun 130022, China;
    2. Editorial Department of Journal of Jilin University(Engineering and Technology Edition), Jilin University, Changchun 130022, China
  • Received:2011-09-20 Published:2013-06-01

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Abstract:

The robust representation of image is established by Histogram of Oriented Gradient (HOG). According to the processing mechanism of human visual system and the theory of multidimensional space biomimetic informatics, a biomimetic classification and recognition method of human behavior are proposed, which is based on HOG+SVM. The method is evaluated and compared with other commonly used methods. Results show that, for the classification and recognition of human behavior in still image, the proposed methods have better performance in recognizing different kinds of behavior, but the performance in recognizing similar behaviors still needs improvement.

Key words: artificial intelligence, Histogram of Oriented Gradient (HOG), support vector machine(SVM), human behavior, biomimetic recognition

CLC Number: 

  • TP391

[1] Smal I, Draegestein K, Galjart N, et al. Particle filtering for multiple object tracking in dynamic fluorescence microscopy images: application to microtubule growth analysis[J]. IEEE Trans Med Imaging, 2008, 27(6): 789-804.

[2] 皮文凯, 刘宏, 查红彬. 基于自适应背景模型的全方位视觉人体运动检测[J]. 北京大学学报:自然科学版, 2004, 40(3): 458-464.

[3] 侯志强, 韩崇昭. 视觉跟踪技术综述[J]. 自动化学报, 2006, 32(4): 603-617.

[4] Wang S J, Chen X, Qin H, et al. Double synaptic weight neuron theory and its application[C]//International Conference on Advances in Natural Computation, Changsha, China, 2005, 264-272.

[5] Weber M, Welling M, Perona P. Towards automatic discovery of object categories[C]//IEEE Conference on Computer Vision and Pattern Recognition, 2000.

[6] Zhang J, Marszalek M, Lazebnik S, et al. Local features and kernels for classification of texture and object categories: A comprehensive study[J]. International Journal of Computer Vision, 2007, 73(2): 213-238.

[7] 谭菊. 基于视觉感知的目标特性分析. 重庆: 重庆大学自动化学院, 2010.

[8] Ikizler N, Cinbis R G, Pehlivan S, et al. Recognizing Actions from Still Images[C]//19th International Conference on Pattern Recognition (ICPR), 2008:1-4.

[9] Yang Wei-long, Wang Yang, Mori Greg, et al. Recognizing Human Actions from Still Images with Latent Poses[C]//2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010: 2030-2037.

[10] Delaitre V, Laptev I, Sivic J. Recognizing human actions in still images: a study of bag-of-features and part-based representations[C]//Proceedings of the British Machine Vision Conference, 2010: 1-11.
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