@inproceedings{f325e04c8b5e45f8a15c32dd6e05b344,
title = "Adaptive and discriminative metric differential tracking",
abstract = "Matching the visual appearances of the target over consecutive image frames is the most critical issue in video-based object tracking. Choosing an appropriate distance metric for matching determines its accuracy and robustness, and significantly influences the tracking performance. This paper presents a new tracking approach that incorporates adaptive metric into differential tracking method. This new approach automatically learns an optimal distance metric for more accurate matching, and obtains a closed-form analytical solution to motion estimation and differential tracking. Extensive experiments validate the effectiveness of adaptive metric, and demonstrate the improved performance of the proposed new tracking method.",
author = "Nan Jiang and Wenyu Liu and Ying Wu",
year = "2011",
doi = "10.1109/CVPR.2011.5995716",
language = "English (US)",
isbn = "9781457703942",
series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
publisher = "IEEE Computer Society",
pages = "1161--1168",
booktitle = "2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011",
address = "United States",
}