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|a eng
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|a Dibeklioğlu, Hamdi
|e verfasserin
|4 aut
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|a A statistical method for 2-D facial landmarking
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|c 2012
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|a Text
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|a ƒaComputermedien
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|a Date Completed 16.05.2012
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|a Date Revised 20.01.2012
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2011 IEEE
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|a 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)
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|a Journal Article
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|a Salah, Albert Ali
|e verfasserin
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|a Gevers, Theo
|e verfasserin
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|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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|g 21(2012), 2 vom: 01. Feb., Seite 844-58
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