A Bayes nets-based prediction/verification scheme for active visual reconstruction

Abstract

We propose in this paper an active vision approach for performing the 3D reconstruction of polyhedral scenes. To perform the reconstruction we use a structure from controlled motion method which allows an accurate estimation of primitive parameters. As this method is based on particular camera motions, perceptual strategies able to appropriately perform a succession of such individual primitive reconstructions are proposed in order to recover the complete spatial structure of complex scenes. The algorithm described in this paper is based on the use of a prediction/verification scheme managed using decision theory and Bayes nets. It allows the visual system to get a more complete high level description of the scene.