Object Tracking via Online Metric Learning | |
Cong Y(丛杨)![]() ![]() | |
2012 | |
会议名称 | 2012 IEEE International Conference on Image Processing |
会议日期 | September 30 - October 3, 2012 |
会议地点 | Orland, Florida, USA |
关键词 | tracking metric learning semi-supervised learning online learning |
页码 | 417-420 |
通讯作者 | 丛杨 |
中文摘要 | By considering visual tracking as a similarity matching problem, we propose a self-supervised tracking method that incorporates adaptive metric learning and semi-supervised learning into the framework of object tracking. For object representation, the spatial-pyramid structure is applied by fusing both the shape and texture cues as descriptors. A metric learner is adaptively trained online to best distinguish the foreground object and background, and a new bi-linear graph is defined accordingly to propagate the label of each sample. Then high-confident samples are collected to self-update the model to handle large-scale issue. Experiments on the benchmark dataset and comparisons with the state-of-the-art methods validate the advantages of our algorithm. |
收录类别 | EI ; CPCI(ISTP) |
产权排序 | 1 |
会议主办者 | IEEE Signal Processing Society |
会议录 | Proceedings of the 2012 IEEE International Conference on Image Processing
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会议录出版者 | IEEE |
会议录出版地 | New York, USA |
语种 | 英语 |
ISBN号 | 978-1-4673-2533-2 |
WOS记录号 | WOS:000319334900100 |
内容类型 | 会议论文 |
源URL | [http://ir.sia.cn/handle/173321/10212] ![]() |
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 | Cong Y,Yuan JS,Tang YD. Object Tracking via Online Metric Learning[C]. 见:2012 IEEE International Conference on Image Processing. Orland, Florida, USA. September 30 - October 3, 2012. |
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