Typical tracking algorithms exploit temporal coherence, in the sense of expecting only small object motions. Even without exact knowledge of the scene, additional spatial coherence can be exploited by expecting only a rigid 3d motion. Feature tracking will benefit from knowing about this rigidity of the scene, especially if individual features cannot be tracked by themselves due to occlusions or illumination changes. We present and compare different approaches of dealing with the spatial coherence in the context of tracking planar scenes. We also show the benefits in scenes with occlusions and changes in illumination, even without models of these distortions.