Abstract
This chapter provides an introduction to face recognition research. Main steps of face recognition processing are described. Face detection and recognition problems are explained from a face subspace viewpoint. Technology challenges are identified after that. Typical strategies for solving the problems are suggested.
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Notes
- 1.
Most individuals can identify only a few thousand people in real life.
- 2.
The ShenZhen (China)–Hong Kong border is the world’s largest border crossing point, with more than 400 000 crossings every day.
References
Ahonen, T., Hadid, A., Pietikainen, M.: Face recognition with local binary patterns. In: Proceedings of the European Conference on Computer Vision, pp. 469–481. Prague, Czech Republic (2004)
Bartlett, M.S., Lades, H.M., Sejnowski, T.J.: Independent component representations for face recognition. In: Proceedings of the SPIE, Conference on Human Vision and Electronic Imaging III, vol. 3299, pp. 528–539 (1998)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 711–720 (1997)
Bernardin, K., v. d. Camp, F., Stiefelhagen, R.: Automatic person detection and tracking using fuzzy controlled active cameras. In: Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)
Bichsel, M., Pentland, A.P.: Human face recognition and the face image set’s topology. CVGIP, Image Underst. 59, 254–261 (1994)
Brunelli, R., Poggio, T.: Face recognition: Features versus templates. IEEE Trans. Pattern Anal. Mach. Intell. 15(10), 1042–1052 (1993)
Cao, Z., Yin, Q., Tang, X., Sun, J.: Face recognition with learning-based descriptor. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2010)
Chellappa, R., Wilson, C., Sirohey, S.: Human and machine recognition of faces: A survey. Proc. IEEE 83, 705–740 (1995)
Cox, I.J., Ghosn, J., Yianilos, P.: Feature-based face recognition using mixture-distance. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 209–216 (1996)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 886–893 (2005)
Dedeoglu, G., Kanade, T., August, J.: High-zoom video hallucination by exploiting spatio-temporal regularities. In: Proceedings of IEEE International Conference on Computer Vision, pp. 151–158 (2004)
Etemad, K., Chellapa, R.: Face recognition using discriminant eigenvectors. In: Proceedings of the International Conference on Acoustic, Speech and Signal Processing (1996)
Goldstein, A.J., Harmon, L.D., Lesk, A.B.: Identification of human faces. Proc. IEEE 59(5), 748–760 (1971)
Hampapur, A., Pankanti, S., Senior, A., Tian, Y.-L., Brown, L., Bolle, R.: Face cataloger: multi-scale imaging for relating identity to location. In: Proc. IEEE Conference Advanced Video and Signal Based Surveillance, pp. 13–20 (2003)
He, X., Yan, S., Hu, Y., Niyogi, P., Zhang, H.: Face recognition using laplacianfaces. IEEE Trans. Pattern Anal. Mach. Intell. 27(3), 328–340 (2005)
Hietmeyer, R.: Biometric identification promises fast and secure processing of airline passengers. ICAO J. 55(9), 10–11 (2000)
Hsu, R.-L.: Face detection and modeling for recognition. PhD thesis, Michigan State University (2002)
Kanade, T.: Picture processing system by computer complex and recognition of human faces. PhD thesis, Kyoto University (1973)
Kirby, M., Sirovich, L.: Application of the Karhunen-Loeve procedure for the characterization of human faces. IEEE Trans. Pattern Anal. Mach. Intell. 12(1), 103–108 (1990)
Kumar, R., Banerjee, A., Vemuri, B.: Volterrafaces: discriminant analysis using Volterra kernels. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 150–155 (2009)
Lades, M., Vorbruggen, J., Buhmann, J., Lange, J., von der Malsburg, C., Wurtz, R.P., Konen, W.: Distortion invariant object recognition in the dynamic link architecture. IEEE Trans. Comput. 42, 300–311 (1993)
Lei, Z., Liao, S., Pietikäinen, M., Li, S.Z.: Face recognition by exploring information jointly in space, scale and orientation. IEEE Trans. Image Process. 20(1), 247–256 (2011)
Liao, S., Lei, Z., Zhu, X., Sun, Z., Li, S.Z., Tan, T.: Face recognition using ordinal features. In: Proceedings of IAPR International Conference on Biometrics, pp. 40–46 (2006)
Liao, S., Zhu, X., Lei, Z., Zhang, L., Li, S.Z.: Learning multi-scale block local binary patterns for face recognition. In: Proceedings of IAPR International Conference on Biometrics, pp. 828–837 (2007)
Liu, C.: Capitalize on dimensionality increasing techniques for improving face recognition grand challenge performance. IEEE Trans. Pattern Anal. Mach. Intell. 28(5), 725–737 (2006)
Lowe, D.G.: Object recognition from local scale-invariant features. In: Proceedings of IEEE International Conference on Computer Vision, p. 1150, Los Alamitos, CA (1999)
Machine Readable Travel Documents (MRTD). http://www.icao.int/mrtd/overview/overview.cfm
Marchesotti, L., Piva, S., Turolla, A., Minetti, D., Regazzoni, C.: Cooperative multisensor system for real-time face detection and tracking in uncontrolled conditions. In: Proceedings of SPIE Int’l Conf. Image and Video Communications and Processing (2005)
Mika, S., Ratsch, G., Weston, J., Scholkopf, B., Muller, K.-R.: Fisher discriminant analysis with kernels. In: Neural Networks for Signal Processing IX, pp. 41–48 (1999)
Moses, Y., Adini, Y., Ullman, S.: Face recognition: The problem of compensating for changes in illumination direction. In: Proceedings of the European Conference on Computer Vision, vol. A, pp. 286–296 (1994)
NIST: Face Recognition Vendor Tests (FRVT) (2006). http://www.frvt.org
Park, J., Lee, S.: Stepwise reconstruction of high-resolution facial image based on interpolated morphable face model. In: Proc. Int’l Conf. Audio-and Video-based Biometric Person Authentication, pp. 102–111 (2005)
Penev, P., Atick, J.: Local feature analysis: A general statistical theory for object representation. Neural Syst. 7(3), 477–500 (1996)
Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1090–1104 (2000)
Roweis, S., Saul, L.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(22), 2323–2326 (2000)
Samal, A., Iyengar, P.A.: Automatic recognition and analysis of human faces and facial expressions: A survey. Pattern Recognit. 25, 65–77 (1992)
Schölkopf, B., Smola, A., Müller, K.R.: Nonlinear component analysis as a kernel eigenvalue problem. Neural Comput. 10, 1299–1319 (1999)
Sirovich, L., Kirby, M.: Low-dimensional procedure for the characterization of human faces. J. Opt. Soc. Am. A 4(3), 519–524 (1987)
Tenenbaum, J., Silva, V., Langford, J.: A global geometric framework for nonlinear dimensionality reduction. Science 290(22), 2319–2323 (2000)
Tistarelli, M., Li, S., Chellappa, R. (eds.): Handbook of Remote Biometrics for Surveillance and Security. Springer, Berlin (2009)
Turk, M.: A random walk through eigenspace. IEICE Trans. Inf. Syst. E84-D(12), 1586–1695 (2001)
Turk, M.A., Pentland, A.P.: Eigenfaces for recognition. J. Cogn. Neurosci. 3(1), 71–86 (1991)
Valentin, D., Abdi, H., O’Toole, A.J., Cottrell, G.W.: Connectionist models of face processing: A survey. Pattern Recognit. 27(9), 1209–1230 (1994)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 511 (2001)
Wiskott, L., Fellous, J., Kruger, N., v. d. Malsburg, C.: Face recognition by elastic bunch graph matching. IEEE Trans. Pattern Anal. Mach. Intell. 19(7), 775–779 (1997)
Yang, P., Shan, S., Gao, W., Li, S.Z., Zhang, D.: Face recognition using Ada-boosted Gabor features. In: Proceedings of International Conference on Automatic Face and Gesture Recognition, pp. 356–361 (2004)
Yao, Y., Abidi, B., Kalka, N., Schmid, N., Abidi, M.: Improving long range and high magnification face recognition: Database acquisition, evaluation, and enhancement. Comput. Vis. Image Underst. 111(2), 111–125 (2008)
Zhang, L., Li, S.Z., Qu, Z., Huang, X.: Boosting local feature based classifiers for face recognition. In: Proceedings of First IEEE Workshop on Face Processing in Video, Washington, DC (2004)
Zhang, G., Huang, X., Li, S.Z., Wang, Y., Wu, X.: Boosting local binary pattern (LBP)-based face recognition. In: Li, S.Z., Lai, J., Tan, T., Feng, G., Wang, Y. (eds.) Advances in Biometric Personal Authentication, vol. 3338, pp. 180–187. Springer, Berlin (2005)
Zhao, W., Chellappa, R., Phillips, P., Rosenfeld, A.: Face recognition: A literature survey. ACM Comput. Surv. 399–458 (2003)
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Li, S.Z., Jain, A.K. (2011). Introduction. In: Li, S., Jain, A. (eds) Handbook of Face Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-932-1_1
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