Multi-View Ambient Occlusion for Enhancing Visualization of Raw Scanning Data

Abstract

The correct understanding of the 3D shape is a crucial aspect to improve the 3D scanning process, especially in order to perform high quality and as complete as possible 3D acquisitions on the field. The paper proposes a new technique to enhance the visualization of raw scanning data based on the definition in device space of a Multi-View Ambient Occlusion (MVAO). The approach allows improving the comprehension of the 3D shape of the input geometry and, requiring almost no preprocessing, it can be directly applied to raw captured point clouds. The algorithm has been tested on different datasets: high resolution Time-of-Flight scans and streams of low quality range maps from a depth camera. The results enhance the details perception in the 3D geometry using the multi-view information to make more robust the ambient occlusion estimation.