Abstract
This paper proposes an effective method for face verification using color sparse representation. In the proposed method, sparse representations are separately applied to multiple color bands of face images. The complementary residuals obtained from the multiple color face images are merged by means of score-level fusion, yielding improved discrimination capability for face verification. Experimental results using two public face databases (CMU Multi-PIE and Color FERET) showed that the proposed face verification method is highly robust under challenging conditions, compared to the conventional methods using grayscale sparse representation.
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Jain, A.K., Ross, A., Prabhakar, S.: An Introduction to Biometric Recognition. IEEE Trans. on. Circuits and Systems for Video Technology 14(1), 4–20 (2004)
Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face recognition: A literature survey. Journal of ACM Computing Surveys 35(4), 399–458 (2003)
Duda, R., Hart, P., Stork, D.: Pattern Classification, second edition, 2nd edn. John Wiley & Sons (2001)
Ho, J., Yang, M., Lim, J., Lee, K., Kriegman, D.: Clustering Appearances of Object under Varying Illumination Conditions. In: IEEE Int’l Conf. on Computer Vision and Pattern Recognition (2003)
Vapnik, V.: The Nature of Statistical Learning Theory. Springer (2000)
Wright, J., Yang, A., Ganesh, A., Sastry, S., Ma, Y.: Robust Face Recognition via Sparse Representation. IEEE Trans. on Pattern Analysis and Machine Intelligence 31(2), 210–227 (2009)
Choi, J.Y., Ro, Y.M., Plataniotis, K.N.: Color Face Recognition for Degraded Face Images. IEEE Trans. on Systems, Man, and Cybernetics 39(5), 1217–1230 (2009)
Shih, P., Liu, C.: Improving the Face Recognition Grand Challenge Baseline Performance Using Color Configurations Across Color Spaces. In: Proc. IEEE Int’l Conf. on Image Processing (2006)
Gross, R., Matthews, I., Cohm, J., Kanade, T., Baker, S.: Multi-PIE. In: Proc. IEEE Int’l Conf. on Automatic Face and Gesture Recognition (2008)
Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET Evaluation Methodology for Face Recognition Algorithms. IEEE Trans. on Pattern Analysis and Machine Intelligence 22(10), 1090–1104 (2000)
Ross, A., Jain, A.K.: Information Fusion in Biometrics. Pattern Recognition Letters 24(13), 2115–2125 (2003)
Sanderson, C., Paliwal, K.K.: Fast feature for face authentication under illumination direction changes. Pattern Recognition Letters 24(14), 2409–2419 (2003)
Ahonen, T., Hadid, A., Pietikäinen, M.: Face Description with Local Binary Pattern: Application to Face Recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 28(12), 2037–2041 (2006)
Liu, C., Wechsler, H.: Gabor Feature Based Classification using the Enhanced Fisher Linear Discriminant Model for Face Recognition. IEEE Trans. on Image Processing 11(4), 467–476 (2002)
Jabid, T., Kabir, M.H., Chae, O.: Local Directional Pattern (LDP) for Face Recognition. In: IEEE Int’l Conf. on Consumer Electronics (2010)
Choi, J.Y., Ro, Y.M., Plataniotis, K.N.: Using Colour Local Binary Pattern Features for Face Recognition. In: IEEE Int’l Conf. on Image Processing (2010)
Choi, J.Y., Ro, Y.M., Plataniotis, K.N.: Boosting color feature selection for color face recognition. IEEE Trans. on Image Processing 20(5), 1–10 (2011)
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Shin, W.J., Lee, S.H., Min, HS., Sohn, H., Ro, Y.M. (2013). Face Verification Using Color Sparse Representation. In: Shi, Y.Q., Kim, HJ., Pérez-González, F. (eds) The International Workshop on Digital Forensics and Watermarking 2012. IWDW 2012. Lecture Notes in Computer Science, vol 7809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40099-5_24
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DOI: https://doi.org/10.1007/978-3-642-40099-5_24
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