Length Classification Techniques for Traffic Applications Sample Clauses

Length Classification Techniques for Traffic Applications. There has been considerable interest in vehicle detection via computer vision, especially in crash-avoidance systems and other driver assistance systems; comparatively, there has been much less interest in vehicle classification via computer vision. Nevertheless, several investigations into vehicle classification via computer vision have been conducted recently. Xxx et al. (2001) demonstrated that vehicle dimension could indeed be accurately estimated from a single camera angle through the use of a set of coordinate mapping functions. Through the use of a shadow removal method (important to maintain true vehicle dimensions) and a convex hull to produce a vehicle mask, they were able to estimate vehicle lengths to within 10 percent in every instance. Their method, however, requires camera calibration to map image angles and pixels into real- world dimensions. Furthermore, few vehicle types were tested, and the algorithm was applied in only one location.
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