  The detection of road 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 non-flat 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.
