2D matching of 3D moving objects in color outdoor scenes

This paper describes an object matching system which is able to extract objects of interest from outdoor scenes and match them. Our application (in the domain of IVHS) involves measuring the average travel time in a road network. The extraction of the object of interest is performed by fusing multiple cues including motion, color, edges, and model information. Two objects extracted from images captured by two independent cameras at different times are then matched to evaluate their similarity. Color indexing based on histogram matching is used to avoid matching all possible pairs of objects. To resolve ambiguities, further matching is done by measuring the Hausdorff distance between two sets of edge points. The object matching system was given 2 sets of 40 vehicles. It was able to identify 23 of the 30 correct matches and all the false matches were rejected. Color indexing reduced the number of candidates for a match from 40 to 2. This matching accuracy is adequate to obtain a reliable estimate of the average travel time