Three-dimensional face recognition in the presence of facial expressions: an annotated deformable model approach.
In this paper, we present the computational tools and a hardware prototype for 3D face recognition. Full automation is provided through the use of advanced multistage alignment algorithms, resilience to facial expressions by employing a deformable model framework, and invariance to 3D capture devices through suitable preprocessing steps. In addition, scalability in both time and space is achieved by converting 3D facial scans into compact metadata. We present our results on the largest known, and now publicly available, Face Recognition Grand Challenge 3D facial database consisting of several thousand scans. To the best of our knowledge, this is the highest performance reported on the FRGC v2 database for the 3D modality.
Kakadiaris
Ioannis A
IA
Department of Computer Science, University of Houston, Houston, TX 77204, USA. ikakadia@central.uh.edu
Passalis
Georgios
G
Toderici
George
G
Murtuza
Mohammed N
MN
Lu
Yunliang
Y
Karampatziakis
Nikos
N
Theoharis
Theoharis
T
D000465:Algorithms; D001185:Artificial Intelligence; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D005145:Face / Q000033:anatomy & histology*; D005149:Facial Expression; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity