%0 Journal Article
%T A Statistical Method for 2D Facial Landmarking
%A Hamdi Dibeklioglu
%A Albert Ali Salah
%A Theo Gevers
%J IEEE Transactions on Image Processing
%D 2012
%V 21
%N 2
%@ 1057-7149
%F Hamdi Dibeklioglu2012
%O ALTRES;ISE
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1853), last updated on Wed, 21 Jun 2017 13:09:20 +0200
%X 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).
%U http://dx.doi.org/10.1109/TIP.2011.2163162
%P 844-858