3D Object Reconstruction from Hand-Object Interactions

Recent advances have enabled 3d object reconstruction approaches using a single off-the-shelf RGB-D camera. Al-though these approaches are successful for a wide range of object classes, they rely on stable and distinctive geomet-ric or texture features. Many objects like mechanical parts, toys, household or decorative articles, however, are texture-less and characterized by minimalistic shapes that are sim-ple and symmetric. Existing in-hand scanning systems and 3d reconstruction techniques fail for such symmetric objects in the absence of highly distinctive features. In this work, we show that extracting 3d hand motion for in-hand scanning effectively facilitates the reconstruction of even featureless and highly symmetric objects and we present an approach that fuses the rich additional information of hands into a 3d reconstruction pipeline, significantly contributing to the state-of-the-art of in-hand scanning. 1