3D-objecttracking with a mixed omnidirectional stereo camera system

This paper presents a novel technique of stereo vision based on the combination of an omnidirectional camera and a perspective camera. The technique combines the 360° field of view of the omnidirectional camera with the long field of view of a perspective camera. We describe the setup of such a camera system and how it can be used to achieve 3D-position estimates. Furthermore, we develop a maximum likelihood approach and a Bayesian approach that are able to fuse monocular and binocular observations of the same object to estimate its position and movement and show how this technique can be applied successfully in the RoboCup MiddleSizeLeague.