Abstract
The majority of the existing appearance-based vehicle-detection systems make use of a sliding-window paradigm for vehicle-candidate regions location. In order to locate all vehicle regions with various sizes and shapes, a large number of search windows are generated by a sliding-window paradigm in most vehicle-detection systems. It is desirable to obtain fewer and more precisely located vehicle candidate regions for further detection. For this purpose, a novel graph-based algorithm is proposed to locate the vehicle proposal regions, which estimates the possibility of a vehicle contained in a bounding box. Experimental results on the public traffic analysis data set (KITTI) and PASCAL VOC 2007 show that the proposed region proposal approach leads to better performances compared with popular bottom-up region proposal methods. Moreover, the proposed vehicle-detection system is evaluated on the KITTI data set, which are determined to be satisfactory, even for the images containing vehicles that have undergone scale variations and camera viewpoint changes, as well as for images that were photographed with complex backgrounds.
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