Max-Confidence Boosting With Uncertainty for Visual Tracking
Guo, Wen1,2; Cao, Liangliang3; Han, Tony X.4; Yan, Shuicheng5; Xu, Changsheng2
2015-05-01
发表期刊IEEE TRANSACTIONS ON IMAGE PROCESSING
卷号24期号:5页码:1650-1659
文章类型Article
摘要The challenges in visual tracking call for a method which can reliably recognize the subject of interests in an environment, where the appearance of both the background and the foreground change with time. Many existing studies model this problem as tracking by classification with online updating of the classification models, however, most of them overlook the ambiguity in visual modeling and do not consider the prior information in the tracking process. In this paper, we present a novel visual tracking method called max-confidence boosting (MCB), which explores a new way of online updating ambiguous visual phenomenon. The MCB framework models uncertainty in prior knowledge utilizing the indeterministic labels, which are used in updating models from previous frames and the new frame. Our proposed MCB tracker allows ambiguity in the tracking process and can effectively alleviate the drift problem. Many experimental results in challenging video sequences verify the success of our method, and our MCB tracker outperforms a number of the state-of-the-art tracking by classification methods.
关键词Max-confidence Boosting Semi-supervised Learning Visual Tracking
WOS标题词Science & Technology ; Technology
关键词[WOS]ROBUST TRACKING ; MEAN SHIFT ; FEATURES ; VIEW
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000352087100004
引用统计
被引频次:9[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/8125
专题模式识别国家重点实验室_多媒体计算与图形学
作者单位1.Shandong Business & Technol Univ, Dept Elect Engn, Yantai 264003, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.IBM Watson Res Ctr, New York, NY 10598 USA
4.Univ Missouri, Columbia, MO 65211 USA
5.Natl Univ Singapore, Singapore 119077, Singapore
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Guo, Wen,Cao, Liangliang,Han, Tony X.,et al. Max-Confidence Boosting With Uncertainty for Visual Tracking[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(5):1650-1659.
APA Guo, Wen,Cao, Liangliang,Han, Tony X.,Yan, Shuicheng,&Xu, Changsheng.(2015).Max-Confidence Boosting With Uncertainty for Visual Tracking.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(5),1650-1659.
MLA Guo, Wen,et al."Max-Confidence Boosting With Uncertainty for Visual Tracking".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.5(2015):1650-1659.
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