@inproceedings{76c3c2f9c01546b29620a224aa0b4697,
title = "Context-learning correlation filters for long-term visual tracking",
abstract = "Correlation Filters (CFs) based trackers have recently attracted many researchers' attention because of their high efficiency and robustness. Nevertheless, CFs trackers usually require a cosine window on account of the boundary effects. This allows trackers to distinguish targets in small background areas. In this paper, we propose an online learning algorithm that employs the global context to alleviate the problems. It is based on Passive-Aggressive algorithm that incorporates context information within CFs trackers. In addition, we train an SVM classifier to redetect objects in case of the model drift caused by occlusion and fast motion etc. The results of extensive experiments on a large-scale benchmark dataset show that the proposed tracker outperform the state-of-the-art trackers.",
keywords = "Context, Long-term, Model drift, Online learning, SVM",
author = "Hong Zhang and Bo Rao and Heding Xu and Yifan Yang and Zeyu Zhang",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; 10th International Conference on Graphics and Image Processing, ICGIP 2018 ; Conference date: 12-12-2018 Through 14-12-2018",
year = "2019",
doi = "10.1117/12.2524187",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Hui Yu and Chunming Li and Yifei Pu and Zhigeng Pan",
booktitle = "Tenth International Conference on Graphics and Image Processing, ICGIP 2018",
address = "美国",
}