Scale-Adaptive Visual Tracking with Occlusion Detection

被引：0

作者：

Xu, Yulong ^{[1
]}

Wang, Jiabao ^{[1
]}

Li, Yang ^{[1
]}

Miao, Zhuang ^{[1
]}

He, Ming ^{[1
]}

Zhang, Yafei ^{[1
]}

机构：

[1] PLA Univ Sci & Technol, Coll Command Informat Syst, Nanjing, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF 2016 IEEE 13TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP 2016) | 2016年

关键词：

visual tracking; occlusion detection; correlation filter; scale calculation;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Occlusion is a challenging problem in visual object tracking. Most state-of-the-art trackers may learn the appearance of the occluding target when it becomes occluded by other objects in the scene. This paper proposes a novel approach of detecting occlusion by dividing the target into several patches and computing the peak-to-sidelobe ratio of every response map. Furthermore, our method can calculate the scale factor by finding the maximum response position of each patch. Experiments are performed on several benchmark challenging sequences. And the results show that our approach outperforms state-of-the-art tracking methods while operating in real-time.

引用

页码：938 / 942

页数：5

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