Abstract
Curvature Gabor features have recently been shown to be powerful facial texture descriptors with applications on face recognition. In this paper we introduce their use in facial action unit (AU) detection within a novel framework that combines multiple Local Curvature Gabor Binary Patterns (LCGBP) on different filter sizes and curvature degrees. The proposed system uses the distances of LCGBP histograms between neutral faces and AU containing faces combined with an AU-specific feature selection and classification process. We achieve 98.6% overall accuracy in our tests with the extended Cohn-Kanade database, which is higher than achieved previously by any state-of-the-art method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: Application to face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(12), 2037–2041 (2006)
Arar, N.M., Gao, H., Ekenel, H.K., Akarun, L.: Selection and combination of local gabor classifiers for robust face verification. In: IEEE 5th International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 297–302 (2012)
Chang, C.C., Lin, C.J.: Libsvm: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2(3), 1–27 (2011)
Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(6), 681–685 (2001)
Cristinacce, D., Cootes, T.: Feature detection and tracking with constrained local models. In: Proceedings of the British Machine Vision Conference 2006, pp. 929–938 (2006)
Daugman, J.: Uncertainty relation for resolution in space, spatial frequency and orientation optimized by two-dimensional visual cortex filters. Journal of Opt. Soc. Amer. 2(7), 1160–1169 (1985)
Ekman, P., Friesen, W.: The facial action coding system: A technique for the measurement of facial movement. Consulting Psychologists Press, Inc., San Francisco (1978)
Hwang, W., Huang, X., Noh, K., Kim, J.: Face recognition system using extended curvature gabor classifier bunch for low-resolution face image. In: IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 15–22 (2011)
Kanade, T., Cohn, J., Tian, Y.: Comprehensive database for facial expression analysis. In: Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 46–53 (2000)
Lucey, P., Cohn, J.F., Kanade, T., Saragih, J., Ambadar, Z., Matthews, I.: The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In: IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 94–101 (2010)
Lucey, P., Cohn, J., Matthews, I., Lucey, S., Sridharan, S., Howlett, J., Prkachin, K.: Automatically detecting pain in video through facial action units. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 41(3), 664–674 (2011)
Ojala, T., Pietikainen, M., Harwood, D.: A comparative study of texture measures with classification based on featured distributions. Pattern Recognition 29(1), 51–59 (1996)
Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)
Peters, G., Kruger, N., von der Malsburg, C.: Learning object representations by clustering banana wavelet responses. In: 1st International Workshop on Statistical Techniques in Pattern Recognition, pp. 113–118 (1997)
Saragih, J.M., Lucey, S., Cohn, J.F.: Deformable model fitting by regularized landmark mean-shift. Int. J. Comput. Vision 91(2) (January 2011)
Senechal, T., Bailly, K., Prevost, L.: Automatic facial action detection using histogram variation between emotional states. In: 20th International Conference on Pattern Recognition (ICPR), pp. 3752–3755 (2010)
Senechal, T., Turcot, J., el Kaliouby, R.: Smile or smirk? automatic detection of spontaneous asymmetric smiles to understand viewer experience. In: IEEE International Conference on Automatic Face and Gesture Recognition (2013)
Shan, C., Gong, S., McOwan, P.W.: Facial expression recognition based on Local Binary Patterns: A comprehensive study. Image and Vision Computing 27(6), 803–816 (2009)
Valstar, M.F., Mehu, M., Jiang, B., Pantic, M., Scherer, K.: Meta analysis of the first facial expression recognition challenge. IEEE Transactions on Systems, Man, Cybernetics, Part B: Cybernetics 42(4), 966–979 (2012)
Valstar, M.F., Pantic, M.: Fully automatic recognition of the temporal phases of facial actions. IEEE Transactions on Systems, Man, Cybernetics, Part B: Cybernetics 42(1), 28–43 (2012)
Yuce, A., Sorci, M., Thiran, J.P.: Improved local binary pattern based action unit detection using morphological and bilateral filters. In: IEEE International Conference on Automatic Face and Gesture Recognition (FG) (2013)
Zhang, W., Shan, S., Gao, W., Chen, X., Zhang, H.: Local gabor binary pattern histogram sequence (lgbphs): a novel non-statistical model for face representation and recognition. In: 10th IEEE International Conference on Computer Vision, vol. 1, pp. 786–791 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Yüce, A., Arar, N.M., Thiran, JP. (2013). Multiple Local Curvature Gabor Binary Patterns for Facial Action Recognition. In: Salah, A.A., Hung, H., Aran, O., Gunes, H. (eds) Human Behavior Understanding. HBU 2013. Lecture Notes in Computer Science, vol 8212. Springer, Cham. https://doi.org/10.1007/978-3-319-02714-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-02714-2_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02713-5
Online ISBN: 978-3-319-02714-2
eBook Packages: Computer ScienceComputer Science (R0)