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Abstract

We present a novel approach to create plausible 3D face models from vague recollections or incomplete descriptions. This task plays an important role in police work, where composite facial images of suspects need to be created from vague descriptions given by the eyewitnesses of an incident. Our approach is based on a morphable model of 3D faces and takes into account correlations among facial features based on human anatomy and ethnicity. Using these correlations, unspeci?ed parts of the target face are automatically completed to yield a coherent face model. The system uses a novel paradigm for navigating face space and provides high-level control of facial attributes as well as the possibility to import facial features from a database. In addition, the user can specify a set of attribute constraints that are used to restrict the target face to a residual subspace. These constraints can also be enforced on the example faces in the database, bringing their appearance closer to the mental image of the user, and thus avoiding confusing exposure to entirely different faces. We also propose a novel approach for adapting the system to local populations based on additional image databases that are converted into our 3D representation by automated shape reconstruction. We demonstrate the applicability of our system in a simulated forensic scenario and compare our results with those obtained by a professional forensic artist using state-of-the-art software for creating composite images in police work.