Self-calibrated reconstruction of partially viewed symmetric objects

Traditional stereo reconstruction techniques, based on point correspondences and estimation of the cameras from the fundamental matrix, introduce a four-fold ambiguity. Moreover, there is a projective ambiguity inherent in the fundamental matrix. We show that a symmetric object can be modeled, even under partial occlusion, by a pair of uncalibrated stereo images. This implies that, unlike traditional stereo algorithms, we can extract 3D information from two arbitrary viewpoints, even when there is no left-to-right point correspondences. To demonstrate the effectiveness of the method, we present experimental results on both synthetic and real images.