@inproceedings{77dd4f4597154877926a3406b129ebf0,
title = "Robust object tracking using adaptive multi-features fusion based on local kernel learning",
abstract = "This paper presents a novel multi-features fusion tracking algorithm based on local kernels learning. Histograms of multiple features are extracted based on sub image patches within the target region, and the features fusion weights are calculated respectively for each patch according to the discriminability of features. It means that the same feature employed in different sub image patches gets different weights. In this way, more precise features fusion weights are provided which lead to a more accurate tracking localization. Moreover the spatial information introduced by the sub patches enhances the tracking robustness. A formula for target localization with adaptive multi-features fusion based on local kernels is deduced. Experiments on challenging video sequences demonstrate that the proposed tracking algorithm performs favorably against trackers using usual target representation, without increasing significantly the computational complexity.",
keywords = "Adaptive multiple features fusion, Local kernel, Visual tracking",
author = "Hainan Zhao and Xuan Wang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014 ; Conference date: 27-08-2014 Through 29-08-2014",
year = "2014",
month = dec,
day = "24",
doi = "10.1109/IIH-MSP.2014.89",
language = "英语",
series = "Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "333--336",
editor = "Junzo Watada and Akinori Ito and Jeng-Shyang Pan and Han-Chieh Chao and Chien-Ming Chen",
booktitle = "Proceedings - 2014 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014",
address = "美国",
}