Structured low rank tracker with smoothed regularization
文献类型：会议论文
| 作者 | Fan BJ(范保杰) ; Cong Y(丛杨); Li XM(李小毛); Tang YD(唐延东)
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| 出版日期 | 2016 |
| 会议名称 | 2016 IEEE Visual Communication and Image Processing, VCIP 2016 |
| 会议日期 | November 27-30, 2016 |
| 会议地点 | Chengdu, China |
| 关键词 | object tracking structured low rank label information smoothed regularization iterative reweighed least squares |
| 页码 | 1-4 |
| 通讯作者 | 范保杰 |
| 中文摘要 | In this paper, we propose a structured low rank learning algorithm with smoothed regularization for robust object tracking, under particle filter framework. Specifically, the relationships among the particles are exploited with structured low rank regularization term, and simultaneously handle the outlier using a group sparsity regularization. The label information from training data is incorporated into the tracking objective function as the classification error term and idea coding regularization term respectively. By the smoothed regularization, the developed structured low rank learning based tracker can be efficiently solved by iterative reweighed least squares algorithm(IRLS), and avoids svd operation. Moreover, the collaborate normalized metric is developed to find the best candidate. Compared with some state-of-the-art tracking methods on 50 challenging sequences, the proposed algorithms perform well in terms of accuracy, robustness. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 2 |
| 会议录 | VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-5090-5316-2 |
| WOS记录号 | WOS:000392647500065 |
| 源URL | [http://ir.sia.cn/handle/173321/19877]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 推荐引用方式 GB/T 7714 | Fan BJ,Cong Y,Li XM,et al. Structured low rank tracker with smoothed regularization[C]. 见:2016 IEEE Visual Communication and Image Processing, VCIP 2016. Chengdu, China. November 27-30, 2016. |
入库方式： OAI收割
来源：沈阳自动化研究所
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