@inproceedings{08dc6340d23943ab9c076d7a13578fdf,
title = "Fast object tracking using color histograms and patch differences",
abstract = "A fast visual object tracking algorithm using novel object appearance models is proposed in this work. We develop a color histogram model and a patch difference model to extract color and texture feature vectors, respectively. Then, we apply k-nearest neighbor classifiers to the color and texture feature vectors and obtain the foreground probability map. We then perform a hierarchical mean shift process on the map to identify the object window. Experimental results demonstrate that proposed algorithm outperforms the conventional algorithms in terms of both tracking accuracy and processing speed.",
keywords = "Object tracking, appearance model, k-nearest neighbor, mean shift localization, tracking-by-detection",
author = "Lee, {Dae Youn} and Sim, {Jae Young} and Chang-Su Kim",
year = "2013",
doi = "10.1109/ICIP.2013.6738804",
language = "English",
isbn = "9781479923410",
series = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
publisher = "IEEE Computer Society",
pages = "3905--3908",
booktitle = "2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings",
note = "2013 20th IEEE International Conference on Image Processing, ICIP 2013 ; Conference date: 15-09-2013 Through 18-09-2013",
}