A Differential Volumetric Approach to Multi-View Photometric Stereo

Abstract

Highly accurate 3D volumetric reconstruction is still an open research topic where the main difficulty is usually related to merging some rough estimations with high frequency details. One of the most promising methods is the fusion between multi-view stereo and photometric stereo images. Beside the intrinsic difficulties that multi-view stereo and photometric stereo in order to work reliably, supplementary problems arise when considered together.In this work, we present a volumetric approach to the multi-view photometric stereo problem. The key point of our method is the signed distance field parameterisation and its relation to the surface normal. This is exploited in order to obtain a linear partial differential equation which is solved in a variational framework, that combines multiple images from multiple points of view in a single system. In addition, the volumetric approach is naturally implemented on an octree, which allows for fast ray-tracing that reliably alleviates occlusions and cast shadows.Our approach is evaluated on synthetic and real datasets and achieves state-of-the-art results.

Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach

“…When applying PS this assumption is heavily violated, which makes it difficult to apply a SfM approach out-of-the-box. A similar approach was considered in [36]. This is realized using LEDs soldered to a circuit board which is attached to a camera.…”

“…Only two approaches use RGB-D cameras in combination with multi-view PS [10,62]. The capturing process in [10] is closely related to [36,61], and [62] make use of a turnable. Thus, [10,62] remain limited to their specific setup.…”