Moving vehicle classification

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2013
Duman, Demet
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In recent years intelligent transportation systems have been an active research area in computer vision. The aim of this study is to classify moving vehicles from highway videos taken by stationary uncalibrated cameras. For this study, three types of vehicle classes with different scales are chosen to classify: car, van and truck. The proposed algorithm is composed of foreground/background segmentation, feature extraction and classification steps. In order to classify each vehicle, histogram of oriented gradients (HOG) features which are shape-based descriptors and blob features which are dimension-based descriptors are used in the algorithm. The effects of these features on the classification performance are also evaluated and simulation results are given on different highway videos.
Image processing, Computer vision., Computer algorithms.
http://etd.lib.metu.edu.tr/upload/12616315/index.pdf
https://hdl.handle.net/11511/23037
Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats
D. Duman, “Moving vehicle classification,” M.S. - Master of Science, Middle East Technical University, 2013.
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