From 3D Faces to Biometric Identities

"The recognition of human faces, in presence of pose and illumination. variations, is intrinsically an ill-posed problem. The direct. measurement of the shape for the face surface is now a feasible solution. to overcome this problem and make it well-posed. This paper proposes a. completely automatic algorithm for face registration and matching. The. algorithm is based on the extraction of stable 3D facial features characterizing. the face and the subsequent construction of a signature manifold.. The facial features are extracted by performing a continuous-to-discrete. scale-space analysis. Registration is driven from the matching of triplets. of feature points and the registration error is computed as shape matching. score. A major advantage of the proposed method is that no data. pre-processing is required. Therefore all presented results have been obtained. exclusively from the raw data available from the 3D acquisition. device.. Despite of the high dimensionality of the data (sets of 3D points, possibly. with the associate texture), the signature and hence the template generated. is very small. Therefore, the management of the biometric data. associated to the user data, not only is very robust to environmental. changes, but it is also very compact. This reduces the required storage. and processing resources required to perform the identi\fcation.. The method has been tested against the Bosphorus 3D face database. and the performances compared to the ICP baseline algorithm. Even in. presence of noise in the data, the algorithm proved to be very robust and. reported identi\fcation performances in line with the current state of the. art."