Field-of-View-Enlarged Single-Camera 3-D Shape Reconstruction

This is the authors' abstract. We don't add key points for this paper.

The 3-D shape reconstruction is a hot topic in computational imaging and many related techniques have been developed. However, most of these techniques have a limited field-of-view (FOV), which results in difficulties on general application. In this article, an FOV-enlarged single-camera 3-D shape reconstruction system is proposed. By placing a saccade mirror in the light path, the proposed system generates a series of virtual cameras and reconstructs the object with multiview images. As the virtual cameras have the same resolution with the real camera, the system gets a larger FOV for reconstruction without sacrificing image resolution. Besides, compared with conventional stereovision systems, the proposed system gives a prior of postures of virtual cameras and simplifies the calibration procedure of extrinsic parameters, which makes it a compact and economical system for application. Reconstruction experiments demonstrate that the proposed system provides an FOV-enlarged and accurate 3-D shape reconstruction. Furthermore, the robustness of the system to environmental conditions is also verified by real-life experiments.