Abstract
Face Detection and Recognition is an important surveillance problem to provide citizens’ security. Nowadays, many citizen service areas as airports, railways, security services are starting to use face detection and recognition services because of their practicality and reliability. In our research, we explored face recognition algorithms and described facial recognition process applying Fisherface face recognition algorithm. This process is theoretically justified and tested with real-world outdoor video. The experimental results demonstrate practically applying of face detection from several foreshortenings and recognition results. The given system can be used in building a smart city as a smart city application, also in different organization to ensure security of people.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Collins, R., et al.: A system for video surveillance and monitoring. Technical report. CMU-RI-TR-00-12VSAM, Final Report. Carnegie Mellon University, Pittsburgh, May 2000
Haritaoglu, I., David, H., Larry, S.D.: W4: real time surveillance of People and their Activities. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 809–830 (2000)
Remagnino, P., Jones, G.A., Paragios, N., Regazzoni, C.S.: Video Based Surveillance Systems Computer Vision and Distributed Processing. Kluwer, Norwell (2002). https://doi.org/10.1007/978-1-4615-0913-4
Stauffer, G.: Learning patterns of activity using real-time tracking. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 747–757 (2000)
VACE: Video analysis and content exploitation. http://www.ic-arda.org/InfoExploit/vace/
Jain, A.K., Bolle, R., Pankanti, S. (eds.): Biometrics: Personal Identification in Networked Security. Kluwer Academic Publishers, Norwell (1999)
Wan, Q., et al.: Face description using anisotropic gradient: thermal infrared to visible face recognition. In: Proceedings of Mobile Multimedia/Image Processing, Security, and Applications 2018, SPIE, vol. 10668, p. 106680V, 14 May 2018. https://doi.org/10.1117/12.2304898
Wolf, M.: Image and video analysis. Smart Camera Design, pp. 163–197. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-69523-5_5
Kumar, S., Pandey, A., Satwik, K.S.R.: Deep learning framework for recognition of cattle using muzzle point image pattern. Measurement 116, 1–17 (2018)
Kumar, S., Tiwari, S., Singh, S.K: Face recognition for cattle. In: Proceedings of 3rd IEEE International Conference on Image Information Processing (ICIIP), pp. 65–72 (2015)
Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 1991), pp. 586–591 (1991)
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)
Baudat, G., Anouar, F.: Generalized discriminant analysis using a kernel approach. Neural Comput. 12(10), 2385–2424 (2000)
Muller, K.R., Mika, S., Ratsch, G., Tsuda, K., Scholkopf, B.: An introduction to kernel-based learning algorithms. IEEE Trans. Neural Netw. 12(2), 181–201 (2001)
Kang, M.G., Park, S.C., Park, M.K.: Super-resolution image reconstruction: a technical overview. IEEE Signal Process. Mag. 20, 21–36 (2013)
Suliman, A., Omarov, B.S.: Applying Bayesian regularization for acceleration of Levenberg-Marquardt based neural network training. Int. J. Interact. Multimedia Artif. Intell. 5(1), 68–72 (2018)
Omarov, B., Altayeva, A., Cho, Y.I.: Smart building climate control considering indoor and outdoor parameters. In: Saeed, K., Homenda, W., Chaki, R. (eds.) CISIM 2017. LNCS, vol. 10244, pp. 412–422. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59105-6_35
Altayeva, A., Omarov, B., Cho, I.Y.: Towards smart city platform intelligence: PI decoupling math model for temperature and humidity control. In: 2018 IEEE International Conference on Big Data and Smart Computing (BigComp), pp. 693–696. IEEE January 2018
Altayeva, A., Omarov, B., Cho, I.Y.: Multi-objective optimization for smart building energy and comfort management as a case study of smart city platform. In: 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), pp. 627–628. IEEE December 2017
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Omarov, B. et al. (2019). Applying Face Recognition in Video Surveillance Security Systems. In: Mazzara, M., Bruel, JM., Meyer, B., Petrenko, A. (eds) Software Technology: Methods and Tools. TOOLS 2019. Lecture Notes in Computer Science(), vol 11771. Springer, Cham. https://doi.org/10.1007/978-3-030-29852-4_22
Download citation
DOI: https://doi.org/10.1007/978-3-030-29852-4_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-29851-7
Online ISBN: 978-3-030-29852-4
eBook Packages: Computer ScienceComputer Science (R0)