@inproceedings{Yun2013,
abstract = {This paper presents a binocular PTU (pan-tilt unit) camera video object tracking scheme using the MeanShift algorithm and the runtime disparity estimation. The proposed method is to accommodate the requirement of 3D content generation and accurate tracking in more advanced video surveillance applications. The disparity estimation process for each stereoscopic pair is formulated as an energy minimization problem. The iterative solution procedure is implemented in a course-to-fine manner. The estimated disparity is used to scale the tracking window by the MeanShift algorithm, i.e. the size of the tracking area is adjustable according to its inner disparity, and thus the moving object can be better located by the camera. The program maintains the semi-real-time performance and acceptable accuracy as evaluated on a set of standard test data. In our experiment, two PointGrey cameras are controlled through a PTU device. The disparity estimation process on the recorded tracking video (640×480) achieves 6fps on an ordinary PC (2.66GHz CPU, 4GB RAM). {\textcopyright} 2013 IEEE.},
author = {Ye, Yun and Ci, Song and Liu, Yanwei and Wang, Haohong and Katsaggelos, Aggelos K.},
booktitle = {2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance},
doi = {10.1109/AVSS.2013.6636637},
isbn = {978-1-4799-0703-8},
month = {aug},
pages = {183--188},
publisher = {IEEE},
title = {{Binocular video object tracking with fast disparity estimation}},
url = {http://ieeexplore.ieee.org/document/6636637/},
year = {2013}
}

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