[1] LU C, TANG X. Surpassing human-level face verification performance on LFW with GaussianFace[C]//AAAI 2015: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. Menlo Park, California: AAAI Press, 2015: 3811-3819. [2] WANG Z, MIAO Z, WU Q M J, et al. Low-resolution face recognition: a review[J]. Visual Computer, 2014, 30(4): 359-386. [3] LI B, CHANG H, SHAN S, et al. Low-resolution face recognition via coupled locality preserving mappings[J]. IEEE Signal Processing, 2010, 17(1): 20-23. [4] PARK J S, LEE S W. An example-based face hallucination method for single-frame, low-resolution facial images[J]. IEEE Transactions on Image Processing, 2008, 17(10): 1806-1816. [5] BAKER S, KANADE T. Limits on super-resolution and how to break them[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(9): 1167-1183. [6] LIN Z, SHUM H Y. Fundamental limits of reconstruction-based super resolution algorithms under local translation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(1):83-97. [7] NASROLLAHI K, MOESLUND T B. Extracting a good quality frontal face image from a low-resolution video sequence[J]. Circuits and Systems for Video Technology, 2011, 21(10): 1353-1362. [8] BAKER S, KANADE T. Hallucinating faces[C]//Proceedings of the Fourth IEEE International Conference on IEEE 2000 Automatic Face and Gesture Recognition. Piscataway, NJ: IEEE, 2000: 83-88. [9] FREEMAN W T, PASZTOR E C. Learning low-level vision[J]. International Journal of Computer Vision, 2000, 40(1): 25-47. [10] YANG J, WRIGHT J, HUANG T, et al. Image super-resolution as sparse representation of raw image patches[C]//Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ: IEEE, 2008: 1-8. [11] TURK M, PENTLAND A. Eigenfaces for recognition[J]. Journal of Cognitive Neuroscience, 1991, 3(1): 71-86. [12] BELHUMEUR P N, HESPANHA J P, KRIEGMAN D J, et al. Eigenfaces vs. Fisherfaces: recognition using class specific linear projection[C]//ECCV'96: Proceedings of the 4th European Conference on Computer Vision. Berlin: Springer, 1996: 43-58. [13] HARRIS D, CHRIS J C, KAUFMAN B L, et al. Support vector regression machines[J]. Advances in Neural Information Processing Systems, 1996, 28(7): 391-394. [14] MAIRAL J, ELAD M, SAPIRO G. Sparse representation for color image restoration[J]. IEEE Transactions on Image Processing, 2008, 17(1): 53-69. [15] ZHANG L, YANG M, FENG X. Sparse representation or collaborative representation: which helps face recognition?[C]//Proceedings of the 2011 International Conference on Computer Vision. Washington, DC: IEEE Computer Society, 2011: 471-478. [16] HUANG G. B, ZHU Q Y, SIEW C K. Extreme learning machine: theory and application[J]. Neurocomputting, 2006, 70(1/2/3): 489-501. [17] OLSHAUSEN B A, FIELD D J. Emergence of simple-cell receptive field properties by learning a sparse code for natural images[J]. Nature, 1996, 381(6583): 607-609. [18] KEYS R G. Cubic convolution interpolation for digital image processing[J]. Acoustics, Speech and Signal Processing, 1982, 29(6): 1153-1160. [19] JIANG J, HU R, HAN Z, et al. Position-patch based face hallucination via locality-constrained representation[C]//Proceeding of the 2012 IEEE International Conference on Multimedia and Expo. Piscataway, NJ: IEEE, 2012: 212-217. [20] WRIGHT J, MA Y, MAIRAL J, et al. Sparse representation for computer vision and pattern recognition[J]. Proceedings of the IEEE, 2010, 98(6): 1031-1044. |