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《Control and Decision》 2014-02
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Review of object detection methods based on SVM

GUO Ming-wei;ZHAO Yu-zhou;XIANG Jun-ping;ZHANG Chen-bin;CHEN Zong-hai;Department of Automation,University of Science and Technology of China;  
The purpose of object detection is to detect and locate the object with a certain class from the static image or videos, and many studies simplify the object detection as a binary classification problem. For the reason that the support vector machine(SVM) can solve the pattern recognition problem well, especially the binary classification problem, how to use the SVM in computer vision becomes a hot point of many researchers. The status of object detection methods based on SVM is reviewed by introducing the concept and theory of SVM, the building of object feature model, training process and location of detection box. Finally, the future work of object detection methods based on SVM is discussed.
【Fund】: 国家自然科学基金项目(61005091 61375079)
【CateGory Index】: TP391.41;TP18
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