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| Human Pose Estimation Based on Fusion of HOG and Color Feature |
| HAN Gui-Jin1,2, ZHU Hong1 |
1.School of Automation and Information Engineering, Xi′an University of Technology, Xi′an 710048
2.School of Automation, Xi′an University of Posts and Telecommunications, Xi′an 710121 |
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Abstract Appearance model plays an important role in the human pose estimation. To improve the estimation accuracy, how to set up the appearance model by using the histogram of oriented gradient (HOG) and color features is studied. The sub-classifier for each cell unit of the body part is built by using the support vector data description (SVDD) algorithm, and then the HOG-based appearance model is constructed by the linear combination of sub-classifiers with different weights. The specific location probability is learned by using those states, which has higher similarity with the HOG-based appearance model, and the corresponding color histogram is calculated, which is the color-based appearance model. According to the illumination and the color contrast between the clothing and background in the static image to be proceeded, the weights of two appearance models are determined, and then two appearance models are combined linearly to construct appearance model based on the fusion of the HOG and color features. The proposed appearance model is used for human pose estimation, and the experimental results show it is more effectively and gets higher pose estimation accuracy.
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Received: 23 December 2013
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2014, Vol. 27 
