Appearance Based Vehicle Detection by Radar-Stereo Vision Integration

This paper proposes a novel method for appearance based vehicle detection by employing stereo vision system and radar units. In the vein of utilizing advanced driver assistance systems, detection and tracking of moving objects or particularly vehicles, represents an essential task. For the merits of such application, it has often been suggested to combine multiple sensors with complementary modalities. In accordance, in this work we utilize a stereo vision and two radar units, and fuse the corresponding modalities at the level of detection. Firstly, the algorithm executes the detection procedure based on stereo image solely, generating the information about vehicles’ position. Secondly, the final unique list of vehicles is obtained by overlapping the radar readings with the preliminary list obtained by stereo system. The stereo vision–based detection procedure consists of (i) edge processing plugging in also the information about disparity map, (ii) shape based vehicles’ contour extraction and (iii) preliminary vehicles’ positions generation. Since the radar readings are examined by overlapping them with the list obtained by stereo vision, the proposed algorithm can be considered as high level fusion approach. We analyze the performance of the proposed algorithm by performing the real-world experiment in highly dynamic urban environment, under significant illumination influences caused by sunny weather.