Obstacle detection using combination of disparity and optical flow under around view for driver assistance system

Obstacle detection while driving to prevent a car accident is always an important issue. The optical flow method is employed to detect the obstacles in around view monitor (AVM). However, by using optical flow only, this method sometimes detects error optical flow points. Also, there is no enough feature points to be detected in order to find the region of obstacles. This paper proposes not only combines disparity map and optical flow of the bird's-eye view images in AVM, but also warn drivers that the region of obstacles nearby. We can find the relative heights of each obstacle's feature point by optical flow and use stereo disparity to find the obstacle and its height in the meantime. Furthermore, in the study, using CUDA parallel computation to speed up calculation. Based on the combination of optical flow and stereo disparity information, we can get the region of the obstacles more accurate.