Free-space detection with fish-eye cameras

Advance Driver Assistance Systems (ADAS) have gained huge attention in the last decades. One of the fundamental steps of the video processing chain is the detection of areas where the car can drive through, i.e. free-space. In this paper we present an approach for the detection of free-space which is based on image segmentation and classification of the obtained image segments. For the image segmentation step we use several state-of-the-art approaches. The classification is done by a random-forest classifier trained to label the image segments with one of three geometric classes (ground, sky, vertical) based on spatial, color and shape features. Segments labelled as ground are used to detect the free-space area in front of the car. Furthermore, a comparison of the results obtained by using different segmentation approaches is provided.