Combining Color Features for Real-Time Correlation Tracking

Yulong XU  Zhuang MIAO  Jiabao WANG  Yang LI  Hang LI  Yafei ZHANG  Weiguang XU  Zhisong PAN  

IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.1   pp.225-228
Publication Date: 2017/01/01
Publicized: 2016/10/04
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016EDL8053
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
correlation filter,  color feature,  real-time visual tracking,  

Full Text: PDF>>
Buy this Article

Correlation filter-based approaches achieve competitive results in visual tracking, but the traditional correlation tracking methods failed in mining the color information of the videos. To address this issue, we propose a novel tracker combined with color features in a correlation filter framework, which extracts not only gray but also color information as the feature maps to compute the maximum response location via multi-channel correlation filters. In particular, we modify the label function of the conventional classifier to improve positioning accuracy and employ a discriminative correlation filter to handle scale variations. Experiments are performed on 35 challenging benchmark color sequences. And the results clearly show that our method outperforms state-of-the-art tracking approaches while operating in real-time.