This paper introduces a new technique for modeling textured 3D faces, which can be generated automatically from one or more photographs or modeled directly through an intuitive user interface. The method addresses two key problems in computer-aided face modeling: automatic registration of new face images or 3D face models to an internal face model, and regulating the naturalness of the modeled faces to avoid unrealistic appearances. The authors derive a morphable face model by transforming the shape and texture of a dataset of 3D face models into a vector space representation. New faces and expressions can be modeled by forming linear combinations of prototypes, with constraints derived from the statistics of the example faces guiding manual or automated matching algorithms. The paper demonstrates 3D face reconstructions from single images and their applications for photo-realistic image manipulations, including changes in gender, fullness, and distinctiveness. The morphable face model is a multidimensional 3D morphing function based on the linear combination of a large number of 3D face scans, with a probability distribution imposed to avoid unlikely faces. The correspondence problem is solved through mathematical optimization, and the output is a high-quality 3D face model that can be used for various face manipulations. The paper also discusses previous work and related techniques, and outlines future improvements, including data reduction, extending the database, and incorporating dynamic facial expressions.This paper introduces a new technique for modeling textured 3D faces, which can be generated automatically from one or more photographs or modeled directly through an intuitive user interface. The method addresses two key problems in computer-aided face modeling: automatic registration of new face images or 3D face models to an internal face model, and regulating the naturalness of the modeled faces to avoid unrealistic appearances. The authors derive a morphable face model by transforming the shape and texture of a dataset of 3D face models into a vector space representation. New faces and expressions can be modeled by forming linear combinations of prototypes, with constraints derived from the statistics of the example faces guiding manual or automated matching algorithms. The paper demonstrates 3D face reconstructions from single images and their applications for photo-realistic image manipulations, including changes in gender, fullness, and distinctiveness. The morphable face model is a multidimensional 3D morphing function based on the linear combination of a large number of 3D face scans, with a probability distribution imposed to avoid unlikely faces. The correspondence problem is solved through mathematical optimization, and the output is a high-quality 3D face model that can be used for various face manipulations. The paper also discusses previous work and related techniques, and outlines future improvements, including data reduction, extending the database, and incorporating dynamic facial expressions.