Better Together: Shading Cues and Multi-View Stereo for Reconstruction Depth Optimization

Abstract

Passive reconstruction methods such as traditional multi-view stereo are capable to accurate reconstruction results. However, the depth calculation of multi-view stereo encounters significant difficulties, especially when the corresponding points have some degree of inaccuracy or unreliability. In this paper, we make use of geometric and shading cues information in the multi-view stereo approach to construct a robust energy function, which is also effective to optimize the depth information provided by multi-view stereo. This work improves the accuracy of point cloud depth. we evaluated our algorithm in the famous DTU datasets, and established our own dinosaur datasets. All the data is collected by mobile devices under natural light condition, while the reconstruction results are completed and accurate.