Non-flat Road Detection Based on A Local Descriptor

Abstrct The detection of ground plane and free space remains challenging for non-flat plane, especially with the varying latitudinal and longitudinal slope or in the case of multi-ground plane. In this paper, we propose a framework of the ground plane detection with stereo vision. The main contribution of this paper is a newly proposed descriptor which is implemented in the disparity image to obtain a disparity texture image. The ground plane regions can be distinguished from their surroundings effectively in the disparity texture image. Because the descriptor is implemented in the local area of the image, it can address well the problem of nonflat plane. And we also present a complete framework to detect the ground plane regions base on the disparity texture image with convolutional neural network architecture. Index Terms Ground Plane Detection, Free Space Estimation, Local Descriptor, Stereo Vision, Convolutional Network.