High-speed Tracking with Multi-kernel Correlation Filters | |
Tang, Ming2; Yu, Bin2; Zhang, Fan1; Wang, Jinqiao2 | |
2018-06-18 | |
会议日期 | 2018-6-18--2018-6-22 |
会议地点 | Salt Lake City, Utah, USA |
英文摘要 | Correlation filter (CF) based trackers are currently ranked top in terms of their performances. Nevertheless, only some of them, such as KCF [26] and MKCF [48], are able to exploit the powerful discriminability of non-linear kernels. Although MKCF achieves more powerful discriminability than KCF through introducing multi-kernel learning(MKL) into KCF,its improvementoverKCF is quitelimited and its computational burden increases significantly in comparison with KCF. In this paper, we will introduce the MKL into KCF in a different way than MKCF. We reformulate the MKL version of CF objective function with its |
会议录出版者 | IEEE |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/48834] |
专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
作者单位 | 1.School of Info. & Comm. Eng., Beijing University of Posts and Telecommunications 2.National Lab of Pattern Recognition, Institute of Automation, CAS, Beijing 100190, China |
推荐引用方式 GB/T 7714 | Tang, Ming,Yu, Bin,Zhang, Fan,et al. High-speed Tracking with Multi-kernel Correlation Filters[C]. 见:. Salt Lake City, Utah, USA. 2018-6-18--2018-6-22. |
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