Reanimating real humans: Automatic reconstruction of animated faces from range data

Abstract

Advances in 3D scanning technology have enabled automatic capture of complex 3D models such as human faces with highly detailed surfaces. However, the range data can not be used easily for animatable face modeling due to absence of functional animation structure and dense surface data. This paper presents an automatic facial model adaptation algorithm for reconstruction of animatable individualized 3D facial models from range data. A generic model that represents both the face shape and anatomical structure serves as the starting point for the adaptation algorithm. The global adaptation transforms the generic model to align it with the scan data in the 3D space based the measurements between a set of 3D landmarks. The local adaptation then deforms the skin mesh of the generic model to fit all of its vertices to the scan surface. The underlying muscle structure is automatically adapted and facial texture is transferred. The reconstructed 3D face resembles the shape and col or of real individual and can be animated immediately with the muscle parameters.