Pedestrian Detection Based on Fusion of Millimeter Wave Radar and Vision

Pedestrian protection system plays an important role in perceptual system of unmanned vehicles and Advanced Drive Assistant System. In order to get more details information about surrounding objects, perceptual system of such kind intelligence system is usually equipped with different sensors, so technology to fuse information of heterogeneous sensors is very important. This paper proposed a novel way to fuse the information of radar and image of camera to realize pedestrian detection and acquire its dynamic information. Contribution of this paper are as following First, a new intra-frame cluster algorithm and an inter-frame tracking algorithm are put forward to extract valid target signal from original radar data with noise. Second, to realize radar-vision data space alignment, least square algorithm is used to get the coordinate transformation matrix. Then with the aid of projections of radar points, a flexible strategy to generate region of interest (ROI) is put forward. Furthermore, to further accelerate detection, an improved fast object estimation algorithm is proposed to acquire a more accurate potential target area based on ROI. At last, histogram of gradient (HOG) features of potential area are extracted and support vector machine is used to judge whether it's a pedestrian. The proposed approach is verified through real experimental examples and the trial results show this method is feasible and effective.