Prism-empowered virtual multiview stereo for three-dimensional vision reconstruction

Three-dimensional (3D) vision reconstruction has been an essential approach to scene understanding, which can hardly strike a good balance among compact structures, high resolution, and flexible viewpoints. In this paper, we demonstrate a prism-empowered virtual multiview stereo vision architecture that allows 3D reconstruction with a single stationary camera. A variable-boresight perspective projection model is presented to characterize the multiview image acquisition process using the combination of a camera and a rotational wedge prism. A model-driven 3D reconstruction performance analysis method is further proposed by considering systematic and random errors, from which an error suppression strategy based on cross-view constraints is formulated. Moreover, a flexible multiview stereo matching method is developed by automatically calibrating the prism-driven dynamic virtual camera via motion estimation and intrinsic optimization. It has been validated through experiments that the multiview epipolar geometry constructed from automatic calibration is reliable and robust, therefore enhancing the accuracy of stereo matching and the efficiency of object reconstruction.