An original solution to 3D face recognition, which supports face matching also in the case of probes with varying expressions and missing parts is proposed in this work. Distinguishing traits of the face are captured by first extracting 3D keypoints of the face scan, then measuring how the face surface changes in the neighborhood of the keypoints using a local descriptor. To this end, an adaptation of the meshDOG detector to the case of 3D faces is proposed, together with a multi-ring geometric histogram descriptor. Face similarity is then evaluated by comparing local keypoint descriptors across inlier pairs of matching keypoints between probe and gallery scans. Experiments have been performed on the Bosphorus database, showing competitive results with respect to existing solutions for 3D face biometrics.
Local Descriptors Matching for 3D Face Recognition / S. Berretti; N. Werghi; A. Del Bimbo; P. Pala. - STAMPA. - (2013), pp. 3710-3714. (Intervento presentato al convegno IEEE International Conference on Image Processing (ICIP'13) tenutosi a Melbourne, Australia nel 15-18 Settembre 2013) [10.1109/ICIP.2013.6738765].
Local Descriptors Matching for 3D Face Recognition
BERRETTI, STEFANO;DEL BIMBO, ALBERTO;PALA, PIETRO
2013
Abstract
An original solution to 3D face recognition, which supports face matching also in the case of probes with varying expressions and missing parts is proposed in this work. Distinguishing traits of the face are captured by first extracting 3D keypoints of the face scan, then measuring how the face surface changes in the neighborhood of the keypoints using a local descriptor. To this end, an adaptation of the meshDOG detector to the case of 3D faces is proposed, together with a multi-ring geometric histogram descriptor. Face similarity is then evaluated by comparing local keypoint descriptors across inlier pairs of matching keypoints between probe and gallery scans. Experiments have been performed on the Bosphorus database, showing competitive results with respect to existing solutions for 3D face biometrics.File | Dimensione | Formato | |
---|---|---|---|
icip13.pdf
Accesso chiuso
Tipologia:
Versione finale referata (Postprint, Accepted manuscript)
Licenza:
Tutti i diritti riservati
Dimensione
1.58 MB
Formato
Adobe PDF
|
1.58 MB | Adobe PDF | Richiedi una copia |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.