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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.