期刊
PATTERN RECOGNITION LETTERS
卷 28, 期 13, 页码 1719-1726出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.patrec.2007.04.014
关键词
traffic monitoring; feature extraction; Support Vector Machine; vehicle classification; image analysis
We present a feature-based classifier that distinguishes bicycles from motorcycles in real-world traffic scenes. The algorithm extracts some visual features focusing on the wheel regions of the vehicles. It splits the problem into two sub-cases depending on the computed motion direction. The classification is performed by non-linear Support Vector Machines. Tests lead to a successful vehicle classification rate of 96.7% on video sequences taken from different road junctions in an urban environment. (c) 2007 Elsevier B.V. All rights reserved.
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