Closed circuit television (CCTV) systems are widely used in the video surveillance of inland waterway. A framework of tracking-learning-detection (TLD) is presented and further enhanced to address the problem of ship identification and tracking in the inland waterway CCTV system. A constraint condition for the
eigenvalues is proposed to examine the short-term tracking results so that complexity in calculating normalized cross correlation is avoided. Meanwhile, tracking results for corners in the image are accurately reserved, making the short-term tracking results reliable. Ships can be located accurately by applying cascaded detectors. A template matching method is proposed to ensure accuracy of the algorithm. Extensive experimental results show that the proposed algorithm outperforms the original TLD framework in terms of efficiency, accuracy and robustness.
TENG Fei, LIU Qing, GUO Jian-ming, ZHOU Ya-qi
. Inland Waterway Ship Tracking Using a TLD Framework[J]. Journal of Applied Sciences, 2014
, 32(1)
: 105
-110
.
DOI: 10.3969/j.issn.0255-8297.2014.01.017
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