Knowledge Commons of Institute of Automation,CAS
High-speed Tracking with Multi-kernel Correlation Filters | |
Tang, Ming1; Yu, Bin1; Zhang, Fan2; Wang, Jinqiao1 | |
2018-06-18 | |
会议名称 | IEEE Conference on Computer Vision and Pattern Recognition |
会议日期 | 2018-6-18--2018-6-22 |
会议地点 | Salt Lake City, Utah, USA |
出版者 | IEEE |
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 |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48834 |
专题 | 紫东太初大模型研究中心_图像与视频分析 |
作者单位 | 1.National Lab of Pattern Recognition, Institute of Automation, CAS, Beijing 100190, China 2.School of Info. & Comm. Eng., Beijing University of Posts and Telecommunications |
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]:IEEE,2018. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Tang_High-Speed_Trac(1461KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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