Face Recognition Approaches: A Survey

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Face Recognition (FR) is a significant area in computer vision plus pattern recognition. The face is the easiest mode to discriminate the specific individuality of every other. FR is a particular identification scheme that usages particular features of an individual to recognize the individual's identity. The challenges in FR are aged, facial terms, variations in the imaging surroundings, illumination plus posture of the face.  Specially, in this study firstly we mark an outline of FR that includes definition, types and problems. Secondly, we provided a complete related work of FR.  The objective of this study is to provide a comprehensive outline on the work that has been carried out over the previous spans in the progressing area of FR. This study offers an extensive view of theories, methodologies, up-to-date techniques for FR.


  • Keywords

    Aging; Dictionary; face recognition; Geometry; Template.

  • References

      [1] R. Chellappa, C. L. Wilson, and S. Sirohey. Human and Machine Recognition of Faces: A Survey. Proc. of the IEEE, 83(5):705-740, May 1995.

      [2] Robert J. Baron. Mechanisms of Human Facial Recognition. International Journal of Man-Machine Studies, 15(2):137-178, 1981.

      [3] R. Brunelli and T. Poggio. FR : Features versus Templates. IEEE Tran. on Pattern Analysis and Machine Intelligence, 15(10):1042{1052, October 1993.

      [4] E. Osuna, R. Freund, and F. Girosi. Training Support Vector Machines: An Application to Face Detection. In IEEE Conference on Computer Vision and Pattern Recognition, pages 193-199, 1997.

      [5] Vladimir N. Vapnik. The Nature of Statistical Learning Theory. Springer Verlog, Heidelberg, DE, 1995.

      [6] L. Sirovich and M. Kirby. Low-dimensional Procedure for the Characterization of Human Faces. Journal of Optical Society of America, 4(3):519-524, March 1987.

      [7] Matthew Turk and Alex Paul Pentland. Eigenfaces for Recognition. Journal of Cognitive Neuroscience, 3(1):71-86, 1991.

      [8] Peter N. Belhumeur, Joao P. Hespanha, and David J. Kriegman. Eigenfaces vs. Fisherfaces: Recognition Using Class Speci c Linear Projection. IEEE Tran. on Pattern Analysis and Machine Intelligence, 19(7):711-720, Jul. 1999.

      [9] Bernhard Scholkopf, Alex J. Smola, and Andre Bernhardt. Nonlinear Com-ponent Analysis as a Kernel Eigenvalue Problem. Neural Computation, 10(5):1299-1319, 199

      [10] M. H. Yang. Kernel Eigenfaces vs. Kernel Fisherfaces: FRus-ing Kernel Methods. In IEEE International Conference on Face and Gesture Recognition, pages 215-220, Washington, May 2002.

      [11] A. Jonathan Howell and Hilary Buxton. Invariance in Radial Basis Func-tion Neural Networks in Human Face Classi cation. Neural Processing Letters, 2(3):26-30, 1995.

      [12] Steve Lawrence, C. Lee Giles, Ah Chung Tsoi, and Andrew D. Back. FR : A Convectional Neural Network Approach. IEEE Trans. on Neu-ral Networks, 8(1):98-113, 1998.

      [13] M. J. Er, S. Wu, and J. Lu. FRusing Radial Basis Function (RBF) Neural Networks. In 38th Conference on Decision & Control, pages 2162-2167, Phoenix, Arizona USA, 1999.

      [14] C. E. Thomaz, R. Q. Feitosa, and A. Veiga. Design of Radial Basis Function Network as Classiffer in FRusing Eigenfaces. In Vth Brazilian Symposium on Neural Networks, pages 118-123, 1998.

      [15] Y. Yoshitomi, T. Miyaura, S. Tomito, and S. Kimura. Face Identi cation using Thermal Image Processing. In IEEE International Workshop on Robot and Human Communication, pages 374-379, 1997.

      [16] Andreas Lanitis, Christopher J. Taylor, and Timothy Francis Cootes. Auto-matic Interpretation and Coding of Face Images using Flexible Models. IEEE Tran. on Pattern Analysis and Machine Intelligence, 19(7):743-756, 1997.

      [17] Alan L. Yuille. Deformable Templates for FR . Journal of Cog-nitive Neuroscience, 3(1):59-70, 1991.

      [18] Laurenz Wiskott, Jean-Marc Fellous, Norbert Kruger, and Christoph von der Malsburg. FRby Elastic Bunch Graph Matching. IEEE Tran. on Pattern Analysis and Machine Intelligence, 19(7):775-779, July 1997.

      [19] P. Penev and J. Atick. Local Feature Analysis: A General Statistical Theory for Object Representation. Network: Computation in Neural Systems, 7:477-500, 1996.

      [20] J. Huang. Detection Strategies for FRUsing Learning and Evo-lution. PhD thesis, George Mason University, May 1998.

      [21] B.Yegnanarayana. Arti cial Neural Networks. Prentice-Hall of India, New Delhi, 1999.

      [22] Simon Haykin. Neural networks: A Comprehensive Foundation. Prentice-Hall International, New Jersey, 1999.

      [23] J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma, ``Robust FRvia sparse representation,'' IEEE Trans. Pattern Anal. Mach. Intell., vol. 31, no. 2, pp. 210-227, Feb. 2009.

      [24] K.-K. Huang, D.-Q. Dai, C.-X. Ren, and Z.-R. Lai, ``Discriminative ker nel collaborative representation with locality constrained dictionary for FR ,'' IEEE Trans. Neural Netw. Learn. Syst., vol. 25, no. 5, pp. 1082_1094, May. 2017.

      [25] R. Giryes and M. Elad, ``Sparsity-based poisson denoising with dictionary learning,'' IEEE Trans. Image Process., vol. 23, no. 12, pp. 5057-5069, Dec. 2014.

      [26] Y. C. Chen, C. S. Sastry, V. M. Patel, P. J. Phillips, and R. Chellappa, ``In-plane rotation and scale invariant clustering using dictionaries,'' IEEE Trans. Image Process., vol. 22, no. 6, pp. 2166-2180, Jun. 2013.

      [27] J. Yang, Z. Wang, Z. Lin, S. Cohen, and T. Huang, ``Coupled dictionary training for image super-resolution,'' IEEE Trans. Image Process., vol. 21, no. 8, pp. 3467-3478, Aug. 2012.

      [28] S. Xiang, G. Meng, Y. Wang, C. Pan, and C. Zhang, ``Image deblurring with coupled dictionary learning,'' Int. J. Comput. Vis., vol. 114, no. 2, pp. 248-271, Sep. 2015.

      [29] K. Cao, E. Liu, and A. K. Jain, ``Segmentation and enhancement of latent fingerprints: A coarse to RidgeStructure dictionary,'' IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 9, pp. 1847-1859, Sep. 2014.

      [30] M. Elad, ``Sparse and redundant representation modeling_What next?'' IEEE Signal Process. Lett., vol. 19, no. 12, pp. 922-928, Dec. 2012.

      [31] R. Rubinstein, A. M. Bruckstein, and M. Elad, ``Dictionaries for sparse representation modeling,'' Proc. IEEE, vol. 98, no. 6, pp. 1045-1057, Jun. 2010.

      [32] I. Tosic and P. Frossard, ``Dictionary learning,'' IEEE Signal Process.Mag., vol. 28, no. 2, pp. 27-38, Mar. 2011.

      [33] H. Cheng, Z. Liu, L. Yang, and X. Chen, ``Sparse representation and learning in visual recognition: Theory and applications,'' Signal Process., vol. 93, no. 6, pp. 1408-1425, 2013.

      [34] M. J. Gangeh, A. K. Farahat, A. Ghodsi, and M. S. Kamel. ``Supervised DL and sparse representation-a review.''Feb.2015.

      [35] Z. Zhang, Y. Xu, J. Yang, X. Li, and D. Zhang, ``A survey of sparse representation: Algorithms and applications,'' IEEE Access, vol. 3, no. 1, pp. 490-530, May 2015.

      [36] M. A. Abuzneid and A. Mahmood, "Enhanced Human FRUsing LBPH Descriptor, Multi-KNN, and Back-Propagation Neural Network," in IEEE Access, vol. 6, pp. 20641-20651, 2018.

      [37] C. Qi et al., "Facial Expressions Recognition Based on Cognition and Mapped Binary Patterns," in IEEE Access, vol. 6, pp.18795-18803,2018.

      [38] M. Mahmoud Al Rahhal, M. L. Mekhalfi, M. Guermoui, E. Othman, B. Lei and A. Mahmood, "A Dense Phase Descriptor for Human Ear Recognition," in IEEE Access, vol. 6, pp. 11883-11887, 2018.

      [39] A. Mallikarjuna Reddy, V. Venkata Krishna, L. Sumalatha," FRbased on Cross Diagonal Complete Motif Matrix", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.10, No.3, pp. 59-66, 2018.

      [40] A. Mallikarjuna Reddy, V. Venkata Krishna, L. Sumalatha," FRbased on stable uniform patterns” International Journal of Engineering & Technology, Vol.7 ,No.(2),pp.626-634, 2018.

      [41] B. F. Wu and C. H. Lin, "Adaptive Feature Mapping for Customizing Deep Learning Based Facial Expression Recognition Model," in IEEE Access, vol. 6, pp. 12451-12461, 2018.

      [42] X. Chen, L. Qing, X. He, J. Su and Y. Peng, "From Eyes to Face Synthesis: a New Approach for Human-Centered Smart Surveillance," in IEEE Access, vol. 6, pp. 14567-14575, 2018.

      [43] M. Mei, J. Huang and W. Xiong, "A Discriminant Subspace Learning Based FRMethod," in IEEE Access, vol. 6, pp. 13050-13056, 2018.

      [44] J. Gu, H. Hu and H. Li, "Local robust sparse representation for FRwith single sample per person," in IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 2, pp. 547-554, Mar. 2018.

      [45] H. Wang, J. Hu and W. Deng, "Compressing Fisher Vector for Robust FR ," in IEEE Access, vol. 5, pp. 23157-23165, 2017.

      [46] J. Liang, C. Chen, Y. Yi, X. Xu and M. Ding, "Bilateral Two-Dimensional Neighborhood Preserving Discriminant Embedding for FR ," in IEEE Access, vol. 5, pp. 17201-17212, 2017.

      [47] G. Muhammad, M. Alsulaiman, S. U. Amin, A. Ghoneim and M. F. Alhamid, "A Facial-Expression Monitoring System for Improved Healthcare in Smart Cities," in IEEE Access, vol. 5, pp. 10871-10881, 2017.

      [48] G. Hermosilla Vigneau, J. L. Verdugo, G. Farias Castro, F. Pizarro and E. Vera, "Thermal FRUnder Temporal Variation Conditions," in IEEE Access, vol. 5, pp. 9663-9672, 2017.

      [49] S. Nagpal, M. Singh, R. Singh and M. Vatsa, "Regularized Deep Learning for FRWith Weight Variations," in IEEE Access, vol. 3, pp. 3010-3018, 2015.

      [50] A. Mallikarjuna Reddy, K. SubbaReddy and V. V. Krishna, "Classification of child and adulthood using GLCM based on diagonal LBP," 2015 International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), Davangere, 2015, pp. 857-861.

      [51] A. Mallikarjuna Reddy, V. V. Krishna, L. Sumalatha and S. K. Niranjan, "Facial recognition based on straight angle fuzzy texture unit matrix," 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), Chirala, 2017, pp. 366-372.




Article ID: 20446
DOI: 10.14419/ijet.v7i4.6.20446

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.