Commenced in January 2007
Paper Count: 30135
2.5D Face Recognition Using Gabor Discrete Cosine Transform
Abstract:In this paper, we present a novel 2.5D face recognition method based on Gabor Discrete Cosine Transform (GDCT). In the proposed method, the Gabor filter is applied to extract feature vectors from the texture and the depth information. Then, Discrete Cosine Transform (DCT) is used for dimensionality and redundancy reduction to improve computational efficiency. The system is combined texture and depth information in the decision level, which presents higher performance compared to methods, which use texture and depth information, separately. The proposed algorithm is examined on publically available Bosphorus database including models with pose variation. The experimental results show that the proposed method has a higher performance compared to the benchmark.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1111558Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1354
 A. F. Abate, M. Nappi, D. Riccio, and G. Sabatino, “2D and 3D face Recognition: A Survey,” Pattern Recognition Letters, Vol. 28, no. 14, pp. 1885–1906, 2007.
 T. Ojala, M. Pietikainen, and T. Maenpaa, “Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 971–987, Aug. 2002.
 B. Zhang, Y. Gao, S. Zhao, and J. Liu, “Local Derivative Pattern Versus Local Binary Pattern: Face Recognition with High-Order Local Pattern Descriptor,” IEEE Trans. Image Processing, vol. 19, no. 2, pp. 533-544, Feb. 2010.
 X. Liu and T. Chen, “Pose-Robust Face Recognition Using Geometry Assisted Probabilistic Modeling,” in Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, 2005, pp. 502–509.
 P. Phillips, P. Grother, R. Micheals, D. Blackburn, E. Tabassi, and M. Bone, “Face Recognition Vendor Test 2002” , in Proc. AMFG, 2003.
 X. Zhang, Y. Gao, and M. Leung, “Recognizing Rotated Faces from Frontal and Side Views: An Approach towards Effective Use of Mugshot Databases,” IEEE Trans. Information Forensics and Security, vol. 3, no. 4, pp. 684–697, 2008.
 K. I. Chang, K. W. Bowyer, and P. J. Flynn, “An Evaluation of Multimodal 2D+3D Face Biometrics,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 4, pp. 619-624, Apr. 2005.
 C. Xua, S. Lia, T. Tana, and L. Quan., “Automatic 3D Face Recognition from Depth and Intensity Gabor features,” Pattern Recognition, vol. 42, no. 9, pp. 1895-1905, 2009.
 P. J. Besl and N. D. McKay, “A Method for Registration of 3D Shapes,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239–256, 1992.
 D. Gabor, “Theory of Communication,” J. Inst. Elect. Eng., vol. 93, pp. 429–457, 1946.
 J. Daugman, “Uncertainty relation for Resolution in Space, Spatial Frequency and Orientation Optimized by Two-Dimensional Visual Cortical Filters,” Journal of the Optical Society of America, vol. 2, no. 7, pp. 1160-1169, 1985.
 J. Jones and L.Palmer, “An Evaluation of the Two-Dimensional Gabor Wavelet Model of Simple Receptive Fields in Cat Striate Cortex,” Journal of Neurophysiology, vol. 58, no. 6, pp. 1233–1258, Dec. 1987.
 Z. M. Hafed and M. D. Levine, “Face Recognition Using the Discrete Cosine Transform,” Int. J. Comput. Vis., vol. 43, no. 3, pp. 167–188, 2001.
 T. M. Cover and P. E. Hart,”Nearest Neighbor Pattern Classification,” IEEE Trans. Information Theory, IT-13, vol. 1, pp. 21–27, 1967.
 A. Savran, N. Alyüz, H. Dibeklioğlu, O. Çeliktutan, B. Gökberk, B. Sankur, and L. Akarun, “Bosphorus Database for 3D Face Analysis,” The First COST 2101 Workshop on Biometrics and Identity Management (BIOID 2008), Roskilde University, Denmark, 7-9 May 2008.