Video-based, Occlusion-robust Multi-view Stereo Using Inner-boundary Depths of Textureless Areas

Abstract

Occlusions and poor textures are two main problems in multi-view stereo reconstruction. This paper presents a video-based solution to address both challenges in depth estimation. We focus on reconstructing accurate inner boundaries of visible textureless areas, particularly for occluded background, by leveraging the reliable depths of object edges. This is done by efficiently respecting two local cues with complementary advantages, i.e. smoothness and density of recovered surfaces. The inner-boundary depths are finally utilized to infer dense geometry without wrong connections between objects. This method only relies on low-level techniques, e.g. intra-view interpolation and inter-view propagation of depths. Experiments indicate its superiority in terms of both depth discontinuities near object silhouettes and surface smoothness in homogeneous regions compared to the state of the art.