Track matching by major color histograms matching and post-matching integration

Publication Type:
Journal Article
Citation:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2005, 3617 LNCS pp. 1148 - 1157
Issue Date:
2005-12-01
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In this paper we present a track matching algorithm based on the "major color" histograms matching and the post-matching integration useful for tracking a single object across multiple, limitedly disjoint cameras. First, the Major Color Spectrum Histogram (MCSH) is introduced to represent a moving object in a single frame by its most frequent colors only. Then, a two-directional similarity measurement based on the MCHS is used to measure the similarity of any two given moving objects in single frames. Finally, our track matching algorithm extends the single-frame matching along the objects' tracks by a post-matching integration algorithm. Experimental results presented in this paper show the accuracy of the proposed track matching algorithm: the similarity of two tracks from the same moving objects has proved as high as 95%, while the similarity of two tracks from different moving objects has been kept as low as up to 28%. The post-matching integration step proves able to remove detailed errors occurring at the frame level, thus making track matching more robust and reliable. © Springer-Verlag Berlin Heidelberg 2005.
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