Isodisparity profile processing for real-time 3D obstacle identification

A new isodisparity profile based real-time obstacle detection algorithm is introduced for an autonomous vehicle. The input disparity map is preprocessed with a look-up-table to generate a number of isodisparity profiles which uniformly distributed over the terrain. For each isodisparity profile, row histogram analysis is performed to determine the reference line. Subsampling is then conducted to select only a limited number of profile points for obstacle and slope evaluation. By comparing the row coordinate of a profile point with the corresponding reference point, obstacles are detected with subpixel accuracy. The algorithm has several advantages over other methods: 1) 3D obstacle detection can be achieved by 1D isodisparity profile segmentation; 2) no conversion of disparity map to (x,y,z) image is needed; and 3) regardless the size of the input disparity map, only a predefined number of profiles and profile points are processed for obstacle map generation. The algorithm is 60 times faster than the conventional method and is able to produce obstacle and slope maps in 4 ms from a 320×240 disparity image (Pentium III, 850 MHz PC).