MC-HOG Correlation Tracking with Saliency Proposal

	MC-HOG Correlation Tracking with Saliency Proposal
	Zhu, Guibo4 ; Wang, Jinqiao4 ; Wu, Yi 5; Zhang, Xiaoyu 6; Lu, Hanqing4 ; Jinqiao Wang
	2016
会议名称	The Tirtieth AAAi Conference on Artificial Intelligence
会议录名称	In Proceedings of The Thirtieth AAAI Conference on Artificial Intelligence
会议日期	February 12-17
会议地点	Phoenix, Arizona USA
摘要	Designing effective feature and handling the model drift problem are two important aspects for online visual tracking. For feature representation, gradient and color features are most widely used, but how to effectively combine them for visual tracking is still an open problem. In this paper, we propose a rich feature descriptor, MC-HOG, by leveraging rich gradient information across multiple color channels or spaces. Then MC-HOG features are embedded into the correlation tracking framework to estimate the state of the target. For handling the model drift problem caused by occlusion or distracter, we propose saliency proposals as prior information to provide candidates and reduce background interference. In addition to saliency proposals, a ranking strategy is proposed to determine the importance of these proposals by exploiting the learnt appearance filter, historical preserved object samples and the distracting proposals. In this way, the proposed approach could effectively explore the color-gradient characteristics and alleviate the model drift problem. Extensive evaluations performed on the benchmark dataset show the superiority of the proposed method.
关键词	Visual Tracking Saliency Proposals Mc-hog
收录类别	EI
语种	英语
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/11757
专题	紫东太初大模型研究中心_图像与视频分析
通讯作者	Jinqiao Wang
作者单位	1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 2.B-DAT & CICAEET, School of Information & Control, Nanjing University of Information Science and Technology, Nanjing, 210044, Jiangsu, China 3.Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China 4.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 5.B-DAT & CICAEET, School of Information & Control, Nanjing University of Information Science and Technology, Nanjing, 210044, Jiangsu, China 6.Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Zhu, Guibo,Wang, Jinqiao,Wu, Yi,et al. MC-HOG Correlation Tracking with Saliency Proposal[C],2016.

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