2D–3D synchronous/asynchronous camera fusion for visual odometry

Abstract

We propose a robust and direct 2D–3D registration method for camera synchronization. Once the cameras are synchronized—or for synchronous setups—we also propose a visual odometry framework that benefits from both 2D and 3D acquisitions. Our method does not require a precise set of 2D-to-3D correspondences, handles occlusions and works when the scene is only partially known. It is carried out through a 2D–3D based initial motion estimation followed by a constrained nonlinear optimization for motion refinement. The problems of occlusion and that of missing scene parts are handled by comparing the image-based reconstruction and 3D sensor measurements. The results of our experiments demonstrate that the proposed framework allows to obtain a good initial motion estimate and a significant improvement through refinement.