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Fast Compressive Tracking with Improved Classifiers | |
Luo, Mingqi; Wang, Tuo; Wang, Lihong | |
2016 | |
会议名称 | PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC) |
会议录名称 | IEEE |
页码 | 4627-4632 |
会议日期 | MAY 28-30, 2016 |
会议地点 | Yinchuan, PEOPLES R CHINA |
出版地 | 345 E 47TH ST, NEW YORK, NY 10017 USA |
出版者 | IEEE |
摘要 | Visual tracking in a video is a challenging problem in computer vision. The core component of object tracker based on tracking-by-detection framework is a discriminative classifier, tasked with distinguishing between the target and the surrounding environment. Fast compressive tracking algorithm is utilized to cope with real time tracking which trained a classifier to distinguish foreground and background, however, it does not take into account the influence of previous positive samples, when target occluded, it is easy lead to tracking fail or drifting problem. This paper proposed a new samples extracted method which take the previous positive samples into classifier training, two sub-classifier are trained and combined to a strong classifier which is used to distinguish target. Experimental results demonstrated the effectiveness of our method. |
关键词 | Object tracking Fast compressive tracking Classifier Samples |
URL | 查看原文 |
收录类别 | CPCI ; CPCI-S |
语种 | 英语 |
WOS研究方向 | Automation & Control Systems ; Engineering |
WOS类目 | Automation & Control Systems ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000383222304163 |
原始文献类型 | Proceedings Paper |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.lzufe.edu.cn/handle/39EH0E1M/9723 |
专题 | 兰州财经大学 |
作者单位 | 1.Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Xian 710049, Shanxi, Peoples R China; 2.Lanzhou Commericial Coll, Longqiao Coll, Lanzhou 730101, Peoples R China |
推荐引用方式 GB/T 7714 | Luo, Mingqi,Wang, Tuo,Wang, Lihong. Fast Compressive Tracking with Improved Classifiers[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2016:4627-4632. |
条目包含的文件 | 条目无相关文件。 |
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