This paper presents a fully automated algorithm for reconstructing a textured 3D model of a face from a single photograph or a raw video stream. The algorithm is based on a combination of Support Vector Machines (SVMs) and a Morphable Model of 3D faces. After SVM face detection, individual facial features are detected using a novel regression- and classification-based approach, and probabilistically plausible configurations of features are selected to produce a list of candidates for several facial feature positions. In the next step, the configurations of feature points are evaluated using a novel criterion that is based on a Morphable Model and a combination of linear projections. To make the algorithm robust with respect to head orientation, this process is iterated while the estimate of pose is refined. Finally, the feature points initialize a model-fitting procedure of the Morphable Model. The result is a high resolution 3D surface model.
|Title of host publication||Proc. IEEE International Conference on Automatic Face & Gesture Recognition, 2008|
|Number of pages||8|
|Publication status||Published - 2008|
|Event||8th International Conference on Automatic Face & Gesture Recognition (FG 08), 2008 - Amsterdam, Netherlands|
Duration: 17 Sep 2008 → 19 Sep 2008
|Conference||8th International Conference on Automatic Face & Gesture Recognition (FG 08), 2008|
|Period||17/09/08 → 19/09/08|