Abstract
The paper presents an autonomous video surveillance system for tracking moving objects in a networked camera environment. The system is validated to identify an authenticated users’ vehicle which is provided with unique sticker as well as vehicle registration number. The multi-camera tracking is implemented on the basis of decentralized hand-over procedure between adjacent cameras. The object of interest in the source image is learnt as single tracking instance and eventually shared among other cameras in the network, autonomously. Thus, the moving objects are continuously tracked without the advent of central supervision and it can be scaled up higher for monitoring of vehicle traffic and other remote surveillance applications.
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References
Joshi, K.A., Thakore, D.G.: A survey on moving object detection and tracking in video surveillance system. International Journal of Soft Computing and Engineering 2(3), 44–48 (2012)
Kim, I.S., Choi, H.S., Yi, K.M., Choi, J.Y., Kong, S.G.: Intelligent visual surveillance—a survey. International Journal of Control, Automation and Systems 8(5), 926–939 (2010)
Patel, C., Shah, D., Patel, A.: Automatic number plate recognition system: a survey. International Journal of Computer Application 69(9), 21–33 (2013)
Vinod, M., Sravanthi, T., Reddy, B.: An adaptive algorithm for object tracking and counting. International Journal of Engineering and Innovative Technology 2(4), 64–69 (2012)
Quaritsh, M., Kreuzthaler, M.: Autonomous multicamera tracking on embedded smart camera. EURASIP Journal on embedded system (2006)
Kim, J.S., Yeom, D.H., Joo, Y.H.: Intelligent unmanned anti-theft system using network camera. International Journal of Control, Automation and System 8(5), 967–974 (2010)
Appiah, K., Hunter, A., Owens, J.: Autonomous real time surveillance system with distributed IP cameras. In: 3rd ACM/IEEE International Conference on Distributed Smart Cameras, Como, Italy (2009)
Clarot, P., Ermis, E.B., Jodoin, P.M., Saligrama, V.: Unsupervised camera network structure estimation based on activity. In: 3rd ACM/ IEEE Conference, Como, Italy (2009)
Leistner, C., Sterzacher, A.: Visual online learning in distributed camera networks. In: Second ACM/IEEE International Conference on Distributed Smart Cameras, Stanford, CA, pp. 1–10 (2008)
Chung, K.W.: Adaptive learning for target tracking and true linking discovering across multiple non-overlapping cameras. IEEE Transaction on Multimedia 13(4), 625–638 (2011)
Lin, C.H., Wolf, M., Kout Soukos, X.: System and software architecture of distributed smart cameras. ACM Transaction on Embedded Computing Systems 9(4) (2010)
Shirmo Hammadi, B., Taylor, C.J.: Distributed target tracking using self-localizing smart camera network. In: Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras, New York, USA, pp. 17–24 (2010)
Kulkarni, M., Wadekar, P., Dagale, H.: Real time object tracking system using distributed smart cameras. In: International Conference on Distributed Smart Cameras, Atlanta, USA (2010)
Geetha, B., Gokul, K.: Cloud based anti-vehicle theft by using number plate recognition. International Journal of Engineering Research and General Science 2(2), 147–151 (2014)
Rao, P., Saluia, P., Sharma, N.: Cloud computing for internet of things and sensing based applications. In: Sixth International Conference Sensing Technology (ICST), pp. 374–380 (2012)
Zaslavsky, A., Perera, C., Georgakopoulos, D.: Sensing as a service and big data (2013). http://arxiv.org/abs/1301.0159
Pu, B., Zhou, F., Bai, X.: Particle filter based on color feature with contour information adaptively integrated for object tracking. In: Fourth International Symposium on Computational Intelligent and Design, Hangzhou, pp. 359–364 (2011)
Salhi, A., Jammoussi, A.Y.: Object tracking system using camshift, meanshift and kalman filter. World Academy of Science Engineering and Technology 64, 32–38 (2012)
Divya, K.N., Danti, A.: Recognition of vehicle plate number and retrieval of vehicle owner’s registration details. In: International Journal of Innovation Research in Technology and Science, pp. 61–66 (2012)
Meshram, P., Indurkar, M., Raj, R., Chitare, N.: Automated license plate recognition using regular expression. International Journal of Engineering Research and Application, pp. 18–22 (2014)
Sharma, G., Sood, S., Gaba, G.S., Gupta, N.: Image recognition system using geometric matching and contour detection. Proceedings with International Journal of Computer Applications 51(17), 48–53 (2012)
Hu, W., Zhou, X., Li, W., Luo, W., Zhang, X., Maybank, S.: Active contour based visual tracking by integrating colors, shapes and motions. IEEE Transaction on Image Processing 22(5), 1778–1792 (2013)
Petrosyan, A.: Vision system for disabled people using pattern matching algorithm. In: Proceedings of the Seventh International Conference on Computer Science and Information Technologies, pp. 343–346 (2009)
Zhu, S., Yuille, A.: Region competition unifying snakes, region growing and bayes for multiband image segmentation. IEEE Trans. Pattern Analysis Mech. Intelligent 18(9), 416–423 (1996). Cambridge, MA
Wei, L., Luo, D.: A biologically inspired computational approach to model top-down and bottom-up visual attention. Optik-International Journal for Light and Electron Optics 126(5), 522–529 (2015)
Fajas, F., Farhan, Y., Remya, P.R., Ambadiyil, S.: A neural network based character recognition system for Indian standard high security number plates. International Journal of Image Processing and Visual Communication 11(1), 32–39 (2012)
Rasheed, S., Naeem, A., Ishaq, O.: Automated number plate recognition using hough lines and template matching. In: Proceedings of the World of Congress on Engineering and Computer Science, San Francisco, USA, vol. 1 (2010)
Babu, C.N.K., Nallaperumal, K.: An efficient geometric feature based license plate localization and recognition. International Journal of Imaging Science and Engineering 2(2), 189–194 (2008)
Sodemann, A.A., Ross, M.P., Borghetti, B.J.: A review of anomaly detection in automated surveillance. IEEE Transactions 42, 1257–1272 (2012)
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Venkatesan, R., Raja, P.D.A., Ganesh, A.B. (2016). Unsupervised Learning Based Video Surveillance System Established with Networked Cameras. In: Thampi, S., Bandyopadhyay, S., Krishnan, S., Li, KC., Mosin, S., Ma, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-319-28658-7_51
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DOI: https://doi.org/10.1007/978-3-319-28658-7_51
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