Abstract
In this paper, we propose a face hallucination method using eigentransformation with distortion reduction. Different from most of the proposed methods based on probabilistic models, this method views hallucination as a transformation between different image styles. We use Principal Component Analysis (PCA) to fit the input face image as a linear combination of the low-resolution face images in the training set. The high-resolution image is rendered by replacing the low-resolution training images with the high-resolution ones, while keeping the combination coefficients. Finally, the nonface-like distortion in the hallucination process is reduced by adding constraints to the principal components of the hallucinated face. Experiments show that this method can produce satisfactory result even based on a small training set.
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References
Patti, Sezan, M., Tekalp, A.: Super-resolution Video Reconstruction with Arbitrary Sampling Latices and Nonzero Aperture Time. IEEE Trans. on Image Processing 6(8), 1064–1076 (1997)
Liu, C., Shum, H., Zhang, C.: A Two-Step Approach to Hallucinating Faces: Global Parametric Model and Local Nonparametric Model. In: Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition, pp. 192–198 (2001)
Bonet, J.D.: Multiresolution sampling procedure for analysis and synthesis of texture images. In: Proceedings of SIGGRAPH 1997, pp. 361–368 (1997)
Fukunnaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic Press, London (1991)
Elad, M., Feuer, A.: Super-Resolution Reconstruction of Image Sequences. IEEE Trans. on PAMIÂ 21(9) (1999)
Turk, M., Pentland, A.: Eigenface for Recognition. J. of Cognitive Neuroscience 3(1), 71–86 (1991)
Hardie, R., Barnard, K., Armstrong, E.: Joint MAP registration and high-resolution image estimation using a sequence of undersampled images. IEEE Trans. on Image Processing 6(12), 1621–1633 (1997)
Baker, S., Kanade, T.: Limits on Super-Resolution and How to Break them. IEEE Trans. on PAMI 24(9), 1167–1183 (2002)
Baker, S., Kanade, T.: Hallucinating Faces. In: Proceedings IEEE International Conference on Automatic Face and Gesture Recognition, pp. 83–88 (2000)
Freeman, W.T., Pasztor, E.C.: Learning Low-Level Vision. In: Proceedings of IEEE International Conference on Computer Vision (1999)
Tang, X., Wang, X.: Face Photo Recognition Using Sketch. In: Proceedings of ICIP, pp. 257–260 (2002)
Wang, X., Tang, X.: Face Sketch Recognition. IEEE Transactions on Circuits and Systems for Video Technology, Special Issue on Image- and Video-Based Biometrics 14(1), 50–57 (2004)
Wang, X., Tang, X.: Face Hallucination and Recognition. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, Springer, Heidelberg (2003)
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Wang, X., Tang, X. (2004). Hallucinating Face by Eigentransformation with Distortion Reduction. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_13
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DOI: https://doi.org/10.1007/978-3-540-25948-0_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22146-3
Online ISBN: 978-3-540-25948-0
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