A Statistical Method for 2-D Facial Landmarking

作者：Dibeklioglu Hamdi^*; Salah Albert Ali; Gevers Theo

来源：IEEE Transactions on Image Processing, 2012, 21(2): 844-858.

DOI：10.1109/TIP.2011.2163162

• Facial feature localization
• facial landmarking
• factor analysis
• Gabor wavelet features
• mixture models
• shape prior
• structural analysis

Many 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).

• 出版日期2012-2