Classification of vehicles plays an important role in a traffic monitoring system. In this paper we present a feature-based classifier, which can distinguish bicycles from motorcycles in real world traffic scenes. Basically, the algorithm extracts some visual features focusing on the region corresponding to the wheels of vehicle. It splits the problem into two sub-cases depending on the computed motion direction. The classification is performed by means of a non-linear Support Vector Machine. Tests lead to a successful classification rate of 93% on video sequences taken from different road junctions in an urban environment
Vision-based bicycle/motorcycle classification with Support Vector Machines
Messelodi, Stefano;Modena, Carla Maria
2004-01-01
Abstract
Classification of vehicles plays an important role in a traffic monitoring system. In this paper we present a feature-based classifier, which can distinguish bicycles from motorcycles in real world traffic scenes. Basically, the algorithm extracts some visual features focusing on the region corresponding to the wheels of vehicle. It splits the problem into two sub-cases depending on the computed motion direction. The classification is performed by means of a non-linear Support Vector Machine. Tests lead to a successful classification rate of 93% on video sequences taken from different road junctions in an urban environmentFile in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
