Model-based generation of personalized full-body 3D avatars from uncalibrated multi-view photographs

Abstract

According to a number of studies, the use of personalized avatars in virtual environments can enhance the immersion experience of users and the effectiveness of communication between different players. The benefits of using personalized avatars in conjunction with recent technological developments in Virtual Reality (VR) prompted an increasing demand for low-cost systems that are capable of fast and easy generation of personal avatars for use in VR applications. In this paper we present a novel model-based technique that is capable of generating personalized full-body 3D avatars from orthogonal photographs. The proposed method utilizes a statistical model of human 3D shape and a multi-view statistical 2D shape model of its corresponding silhouettes. Our technique is automatic, requiring minimal user intervention, and does not need a calibrated camera. Each component of our proposed technique is extensively evaluated and validated, in an attempt to test the geometric accuracy and identifiability of generated avatars. Furthermore, we demonstrate the use of the proposed method for generating and importing animation-ready avatars in collaborative VR environments.