Abstract
Human face recognition is one of the most popular biometric approaches. In last decade 3D face recognition attracted much attention. In this paper, we present an automatic face recognition algorithm and demonstrate its performance on the Bosphorus 3D face database. A novel Dynamic mask is used to segment automatically the regions of face which are less sensitive to expressions. We applied a multilayer perceptron (MLP) to compute maskable region (MR). MR shows which percentage of face image pixels must be masked to produce the expression insensitive binary mask for 3D faces. We applied a modified nearest neighbor classifier for identification. We only used one neutral frontal face of each subject as gallery images and tested our algorithm with emotional expression images. The identification rate obtained is 85.36 percent in non-neutral expression.
Chapter PDF
Similar content being viewed by others
References
Abate, A.F., Nappi, M., Riccio, D., Sabatino, G.: 2D and 3D Face Recognition: A survey. Pattern Recognition Letters, 1885–1906 (2007)
Bowyer, K., Chang, K., Flynn, P.: A Survey of approaches and challenges in 3D and multi-model 3D + 2D face recognition. In: CVIU, vol. 101, pp. 1–15 (2006)
Chau, C.S., Han, F., Ho, Y.K.: 3D human face recognition using point signature. Automatic Face and Geusture Recognition, 233—238 (2000)
Zhong, C., Sun, Z., Tan, T.: Robust 3D face recognition using learnd visual codebook. Pattern Recognition, 1–6 (2007)
Queirolo, C.C., Silva, L., Bellon, O.R.P., Segundo, M.P.: 3D face recognition simulated annealing and the surface interpenetration measure. IEEE Transaction, Pattern Analysis and Machine Intelligence 32(2), 206–219 (2010)
Xu, C., Li, S., Tan, T., Quan, L.: Automatic 3D face recognition from depth and intensity Gabor features. Pattern Recognition 42, 1895–1905 (2009)
Mian, A.S., Bennamoun, M., Owens, R.: An efficient multimodal 2D-3D hybrid approach to automatic face recognition. IEEE Transaction, Pattern Analysis and Machine Intelligence 29(11), 1927–1943 (2007)
Besl, P.J., Mckay, N.D.: A method for registration of 3D shapes. IEEE Transaction, Pattern Analysis and Machine Intelligence 14, 39–256 (1992)
Savran, A., Alyüz, N., Dibeklioğlu, H., Çeliktutan, O., Gökberk, B., Sankur, B., Akarun, L.: Bosphorus Database for 3D Face Analysis. In: Schouten, B., Juul, N.C., Drygajlo, A., Tistarelli, M. (eds.) BIOID 2008. LNCS, vol. 5372, pp. 47–56. Springer, Heidelberg (2008)
Ekman, P., Friesen, W.V.: Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto (1978)
Xu, C., Wang, Y., Tan, T., Quan, L.: A new attempt to face recognition using 3D-eigenfaces. In: The 6th Asian Conference on Computer Vision (ACCV), vol. 2, pp. 884–889 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Salahshoor, S., Faez, K. (2012). 3D Face Recognition Using an Expression Insensitive Dynamic Mask. In: Elmoataz, A., Mammass, D., Lezoray, O., Nouboud, F., Aboutajdine, D. (eds) Image and Signal Processing. ICISP 2012. Lecture Notes in Computer Science, vol 7340. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31254-0_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-31254-0_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31253-3
Online ISBN: 978-3-642-31254-0
eBook Packages: Computer ScienceComputer Science (R0)