TY  - JOUR
AU  - Hamdi Dibeklioglu
AU  - Albert Ali Salah
AU  - Theo Gevers
PY  - 2012//
TI  - A Statistical Method for 2D Facial Landmarking
T2  - TIP
JO  - IEEE Transactions on Image Processing
SP  - 844
EP  - 858
VL  - 21
IS  - 2
N2  - IF = 3.32Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in coarse-to-fine fashion and complemented with a shape prior. We assess the accuracy and the robustness of the proposed approach in extensive cross-database conditions conducted on four face data sets (Face Recognition Grand Challenge, Cohn-Kanade, Bosphorus, and BioID). Our method has 99.33% accuracy on the Bosphorus database and 97.62% accuracy on the BioID database on the average, which improves the state of the art. We show that the method is not significantly affected by low-resolution images, small rotations, facial expressions, and natural occlusions such as beard and mustache. We further test the goodness of the landmarks in a facial expression recognition application and report landmarking-induced improvement over baseline on two separate databases for video-based expression recognition (Cohn-Kanade and BU-4DFE).
SN  - 1057-7149
UR  - http://dx.doi.org/10.1109/TIP.2011.2163162
N1  - ALTRES;ISE
ID  - Hamdi Dibeklioglu2012
ER  -