The B2F dataset (Biometric images of Fingerprints and Faces) has been prepared for face and fingerprint recognition, verification or classification.
The first subset (Fingerprint): This set of data presents the five finger feature vectors (of the left hand) for each person in a csv files.
The second subset (Face): This set of data presents feature vectors of face images in csv files. Feature vectors were extracted using the model (ResNet-50 + ArcFace). This set of face feature vectors represents:
"The friction ridge pattern is a 3D structure which, in its natural state, is not deformed by contact with a surface''. Building upon this rather trivial observation, the present work constitutes a first solid step towards a paradigm shift in fingerprint recognition from its very foundations. We explore and evaluate the feasibility to move from current technology operating on 2D images of elastically deformed impressions of the ridge pattern, to a new generation of systems based on full-3D models of the natural nondeformed ridge pattern itself.