par Houben, Quentin ;Tocino Diaz, Juan Carlos ;Warzée, Nadine ;Debeir, Olivier ;Czyz, Jacek
Référence VISAPP 2009(Lisboa, Portugal), VISAPP 2009 : International Conference on Computer Vision Theory and Applications
Publication Publié, 2009-02-01
Publication dans des actes
Résumé : This paper presents a method for counting and classifying vehicles on motorway. The system is based on a multi-camera system fixed over the road. Different features (maximum phase congruency and edges) are detected on the two images and matched together with local matching algorithm. The resulting 3D points cloud is processed by maximum spanning tree clustering algorithm to group the points into vehicle objects. Bounding boxes are defined for each detected object, giving an approximation of the vehicles 3D sizes. A complementary 2D quadrilateral detector has been developed to enhance the probability of matching features on vehicle exhibiting little texture such as long vehicles. The algorithm presented here was validated manually and gives 90% of good detection accuracy.