The automated handling of objects requires the estimation of object position and rotation with respect to an actuator. We propose a system for silhouette-based pose estimation, which can be applied to a variety of objects, including untextured and slightly transparent objects. Pose estimation inevitably relies on previous knowledge of the object's 3D geometry. In contrast to traditional view-based approaches our system creates the required 3D model solely from the object silhouettes and abandons the need to obtain a model beforehand. It is sufficient to rotate the object in front of the catadioptric camera system. Experimental results show that the pose estimation accuracy drops only slightly compared to a highly accurate input model. The whole system utilizes the parallel processing power of graphics cards, to deliver an auto calibration in 20 s and reconstructions and pose estimations in 200 ms.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.