Multi-view depth estimation based on visual-hull enhanced Hybrid Recursive Matching for 3D video conference systems

This paper discusses the problem of high quality depth map estimation for real-time systems. Our work is based on the European FP7 project 3DPresence which aims to build a multi-view and multiuser 3D videoconferencing system. Based on new multi-view auto-stereoscopic display technology the remote conferees will be rendered as an integral part of a three dimensional virtual shared environment. In order to create the related views for the 3D displays as well as to virtually correct the eye contact problem robust depth maps are required. For this purpose, in this paper we will discuss the fusion of two competing approaches which have, from a camera configuration point of view, contrary to each other properties. Namely, we will combine the volumetric Visual Hull (VH) approach with the stereo matching based Hybrid Recursive Matching (HRM) to a new method which benefits from the advantages of both techniques and discards their weak points.