Estimation of Road Surface Plane and Object Height Focusing on the Division Scale in Disparity Image Using Fisheye Stereo Camera

In this paper, we propose a novel algorithm for estimating road surface shapes and object heights using a fisheye stereo camera. Environmental recognition is an important task for advanced driver-assistance systems. However, previous studies have only achieved narrow measurement ranges owing to sensor restrictions. Moreover, the previous approaches cannot be used in environments where the slope changes because they assume inflexible constraints on the road surfaces. We use a fisheye stereo camera capable of measuring wide and dense 3D information and design a novel algorithm by focusing on the degree of division in a disparity image to overcome these defects. Experiments show that our method can detect an object in various environments, including those with inclined road surfaces.