Combating Occlusion and Scene Changes for Camera Position Determination

The determination of camera position via eigenspace methods has been applied recently to robot navigation and visual servoing. Conventional eigenspace methods are not robust to occlusion and scene changes due to their global nature. This paper describes techniques for performing robust camera position determination. Input images are divided into separate local areas, with camera position de-termined through eigenspace analysis for each area individually. The positions of occluded sections are ignored in determining the final camera position. The detection of occluded sections is determined by applying a threshold to the eigenspace reconstruc-tion error of the input images. Experiments were performed determining the translational position of a camera and analyzing the magnitude of the errors caused by occlusion, the ability to detect different size occlusions and the accuracy improvement pro-vided by the subsectioning technique.