Virtual Reality Group

Figure 1: Camera setup optimization sequence for a five sided CAVE with four cameras. The camera positions were constrained to remain on the open top side of the CAVE. Notice the increased point sample density in head height to improve the head-tracking robustness. We propose a method to determine the optimal camera alignment for a tracking system with multiple cameras by specifying the vol-ume to be tracked and an initial camera setup. We use optimiza-tion strategies based on methods usually employed for solving non-linear systems of equations. All approaches are fully automatic and take advantage of modern graphics hardware since we also imple-ment a GPU-based, accelerated visibility test. The algorithm au-tomatically optimizes the whole setup by adjusting the given set of camera parameters. We can steer the optimization towards different goals depending on the desired application, e.g. the widest possi-ble volume coverage or maximum camera visibility to overcome heavy occlusion problems during the tracking process. We also consider parameter constraints that the user may specify accord-ing to restrictions in the local environment where the cameras have to be mounted. This allows for a convenient definition of higher level constraints for the camera setup