Real–time 3-D surface reconstruction from multiple cameras

Abstract

Recently, by means of the cheap GPUs and appropriate parallel algorithms, it is possible to perform real-time 3-D reconstruction. In this paper, a realtime 3-D surface reconstruction system has been set up to achieve dense geometry reconstruction from multiple cameras. Pose of the cameras are accurately estimated with the help of a self-calibration system. The depth map of the recorded scene is computed by means of a dense multi-view stereo algorithm. Matching cost aggregation and global optimization method are used to obtain the accurate depth values. We merge our works into the Meshlab, where the depth information is used for generating the surface model. High-quality results are finally presented to prove the feasibility of our system and reconstruction algorithms.