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.
CITATION STYLE
Cheng, E. D., & Piccardi, M. (2005). Track matching by major color histograms matching and post-matching integration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3617 LNCS, pp. 1148–1157). https://doi.org/10.1007/11553595_141
Mendeley helps you to discover research relevant for your work.