Robust Surface Light Field Modeling

Abstract

Surface light field advances conventional light field rendering techniques by utilizing geometry information. Using surface light field, real-world objects with complex appearance could be faithfully represented. This capability could play an important role in many VR/AR applications. However, an accurate geometric model is needed for surface light field sampling and processing, which limits its wide usage since many objects of interests are difficult if not impossible to reconstruct with their usually very complex appearances. We propose a novel optimization framework to reduce the dependency of accurate geometry. The key insight is to treat surface light sampling as a multi-view multi-texture optimization problem. Our approach can deal with both model inaccuracy and texture to model misalignment, making it possible to create high-fidelity surface light field models without using high-precision special hardware.