Chaotic Features for Traffic Video Classification

• Yong Wang,
• Shiqiang Hu,

Vol. 8, No. 8, August 28, 2014
10.3837/tiis.2014.08.015, Download Paper (Free):

• Traffic video classification
• Chaotic features
• Earth mover’s distance

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.

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