Environment modeling with stereo vision

We consider the problem of creating compact surface-based environment models from stereo vision images taken from a stereo-camera equipped mobile robot. The stereo images can be quite complex and correlation stereo suffers from considerable noise at ranges over a few metres. We construct the environment models by segmenting the scene viewed from a stereo camera into rectangular planar surfaces through the use of the patchlets surface element data structure. Patchlets are the projection of the stereo pixels onto detected surfaces in the scene. They have position, orientation, size and sensor-based confidence measures. The confidence measures allow proper weighting of patchlet parameters when aggregating patchlets into larger surfaces.