Ground plane segmentation from multiple visual cues

Abstract

An approach which uses multiple sources of visual information (or visual cues) to identify and segment the ground plane in indoor mobile robot visual navigation applications is presented. Information from color, contours and corners and their motion are applied, in conjunction with planar homography relations, to identify the navigable area of the ground, which may be textured or non-textured. We have developed new algorithms for both the computation of the homography, in which a highly stable two point method for pure translation is proposed, and the region growing. Also, a new method for applying the homography to measure the height of a visual feature to the ground using an uncalibrated camera is also developed. Regions are segmented by color and also by their sizes and geometric relation and these region boundarys are extracted as contours. By controlled manoeuvres of a mobile robot, the methods of coplanar feature grouping developed in this paper are not only applicable to corner correspondences but also to contours. This leads to robust, accurate segmentation of the ground plane from the other image regions. Results are presented which show the validity of the approach.