TY - GEN
T1 - Towards 3D-aided profile-based face recognition
AU - Efraty, B. A.
AU - Ismailov, E.
AU - Shah, S.
AU - Kakadiaris, I. A.
N1 - Funding Information:
This work was supportedb y grants from NATO (CRG 971494), Fundaci6n Ram& Areces (Spain), MEC (Spain, PB97-1123), INSERM (CRI 9806, France) and Conseil RCgional d’Aquitaine (France).M . Trujillo is the recipiento f a fellowship from Fundaci6n Ram6n Areces.
PY - 2009
Y1 - 2009
N2 - In this paper, we present a fully automatic system for face recognition based on a silhouette of the face profile. Previous research has demonstrated the high discriminative potential of this biometric. However, for the successful employment of this characteristic one is confronted with many challenges, such as the sensitivity of a profile's geometry to face rotation and the difficulty of accurate profile extraction from images. We propose to explore the feature space of profiles under various rotations with the aid of a 3D face model. In the enrollment mode, 3D data of subjects are acquired and used to create profiles under different rotations. The features extracted from these profiles are used to train a classifier. In the identification mode, the profiles are extracted from side view images using a modified Active Shape Model approach. We validate the accuracy of the extractor and the robustness of classification algorithms using data from a publicly available database.
AB - In this paper, we present a fully automatic system for face recognition based on a silhouette of the face profile. Previous research has demonstrated the high discriminative potential of this biometric. However, for the successful employment of this characteristic one is confronted with many challenges, such as the sensitivity of a profile's geometry to face rotation and the difficulty of accurate profile extraction from images. We propose to explore the feature space of profiles under various rotations with the aid of a 3D face model. In the enrollment mode, 3D data of subjects are acquired and used to create profiles under different rotations. The features extracted from these profiles are used to train a classifier. In the identification mode, the profiles are extracted from side view images using a modified Active Shape Model approach. We validate the accuracy of the extractor and the robustness of classification algorithms using data from a publicly available database.
KW - 3D
KW - Active shape model
KW - Face profile extraction
KW - Facial data
KW - Profile-based face recognition
UR - http://www.scopus.com/inward/record.url?scp=71749108741&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71749108741&partnerID=8YFLogxK
U2 - 10.1109/BTAS.2009.5339078
DO - 10.1109/BTAS.2009.5339078
M3 - Conference contribution
AN - SCOPUS:71749108741
SN - 9781424450206
T3 - IEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009
BT - IEEE 3rd International Conference on Biometrics
T2 - IEEE 3rd International Conference on Biometrics: Theory, Applications and Systems, BTAS 2009
Y2 - 28 September 2009 through 30 September 2009
ER -