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http://dx.doi.org/10.3837/tiis.2014.08.015

Chaotic Features for Traffic Video Classification  

Wang, Yong (School of Aeronautics and Astronautics, Shanghai Jiao Tong University)
Hu, Shiqiang (School of Aeronautics and Astronautics, Shanghai Jiao Tong University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.8, no.8, 2014 , pp. 2833-2850 More about this Journal
Abstract
This paper proposes a novel framework for traffic video classification based on chaotic features. First, each pixel intensity series in the video is modeled as a time series. Second, the chaos theory is employed to generate chaotic features. Each video is then represented by a feature vector matrix. Third, the mean shift clustering algorithm is used to cluster the feature vectors. Finally, the earth mover's distance (EMD) is employed to obtain a distance matrix by comparing the similarity based on the segmentation results. The distance matrix is transformed into a matching matrix, which is evaluated in the classification task. Experimental results show good traffic video classification performance, with robustness to environmental conditions, such as occlusions and variable lighting.
Keywords
Traffic video classification; Chaotic features; Earth mover's distance;
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Times Cited By KSCI : 2  (Citation Analysis)
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