Smooth mesh generation from noisy depth image

Abstract

This paper presents a plausible real-time smooth mesh generation method from real scene images, captured from a conventional color and depth camera. We perform statistical outlier removal method to detect holes for the captured raw depth image and fill the detected holes with the weighted mean values of its neighbors. The 3D surface mesh of the real scene is then reconstructed. The initially generated noisy mesh is filtered with our novel multi-weight depth refinement algorithm. The entire pipeline is fully automated from capturing to mesh generation and working at interactive frame rates. Robust results are shown even in the dynamic scene captured from the moving camera.