Max-Confidence Boosting With Uncertainty for Visual Tracking
文献类型：期刊论文
| 作者 | Guo, Wen1,2; Cao, Liangliang3; Han, Tony X.4; Yan, Shuicheng5; Xu, Changsheng2
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| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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| 出版日期 | 2015-05-01 |
| 卷号 | 24期号:5页码:1650-1659 |
| 关键词 | Max-confidence boosting semi-supervised learning visual tracking |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | ROBUST TRACKING ; MEAN SHIFT ; FEATURES ; VIEW |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000352087100004 |
| 公开日期 | 2015-09-22 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/8125]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队 |
| 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 |
| 推荐引用方式 GB/T 7714 | 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. |
入库方式： OAI收割
来源：自动化研究所
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