Abstract

Images formed by a human face change with viewpoint. A new technique is described for synthesizing images of faces from new viewpoints, when only a single 2D image is available. A novel 2D image of a face can be computed without knowledge about the 3D structure of the head. The technique draws on a single generic 3D model of a human head and on prior knowledge of faces based on example images of other faces seen in different poses. The example images are used to "learn" a pose-invariant shape and texture description of a new face. The 3D model is used to solve the correspondence problem between images showing faces in different poses. Examples of synthetic "rotations" over 24 ffi based on a training set of 100 faces are shown. This document is available as /pub/mpi-memos/TR-026.ps.Z via anonymous ftp from ftp.mpik-tueb.mpg.de or from the World Wide Web, http://www.mpik-tueb.mpg.de/projects/TechReport/list.html. 1 Introduction Given only a driver's license photograph of a person's ...

Citations