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Real Time Surveillance and Object Tracking

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Smart Trends in Information Technology and Computer Communications (SmartCom 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 876))

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Abstract

Object tracking is a challenging task in surveillance and activity analysis. Autonomous video surveillance and monitoring has a rich history in real time object tracking. It has many application in different area like home automation, military, in surveillance monitoring as well as in search-and-rescue operations. Main objective is tracking a particular target or object from real time videos and transmit it to one place to another place. Raspberry pi is used as processor. Video transport has technical challenge when the wireless transmissions require high data rate and low latency.

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References

  1. Comaniciu, D., Ramesh, V., Meer, P.: Real-time tracking of non-rigid objects using mean shift. In: IEEE Proceedings of CVPR (2000)

    Google Scholar 

  2. Zou, X., Wang, W., Kittler, J.: Non-negative matrix factorization for face illumination analysis. The University of Liverpool (2008)

    Google Scholar 

  3. Wu, Y., Shen, B., Ling, H.: Visual tracking via online nonnegative matrix factorization. IEEE Trans. Circuits Syst. Video Technol. 24, 374–383 (2014)

    Article  Google Scholar 

  4. Buciu, I., Nafornita, I.: Non-negative matrix factorization methods for face recognition under extreme lighting variations. In: International Symposium on Signals, Circuits and Systems (ISSCS) (2009)

    Google Scholar 

  5. Wang, J., Yagi, Y.: Integrating color and shape-texture features for adaptive real-time object tracking 17 (1999)

    Google Scholar 

  6. Nawaz, T., Cavallaro, A.: A protocol for evaluating video trackers. In: IEEE Proceedings on ICIP (2011)

    Google Scholar 

  7. Hong, L., Ze, Y., Hongbin, Z., Yuexian, Z., Zhang, L.: Robust human tracking based on multi-cue integration and mean-shift. Pattern Recogn. Lett. 30, 827–837 (2009)

    Article  Google Scholar 

  8. Moreno-Noguer, F., Sanfeliu, A., Samaras, D.: Integration of deformable contours and a multiple hypotheses Fisher color model for robust tracking in varying illuminant environments. Image Vis. Comput. 25, 285–296 (2007)

    Article  Google Scholar 

  9. Yu, G., Lu, H.: Illumination invariant object tracking with incremental subspace learning. In: Conference on ICIG (2009)

    Google Scholar 

  10. Deilamani, M., Asli, R.: Moving object tracking based on mean shift algorithm and features fusion. In: International Conference on AISP (2011)

    Google Scholar 

  11. Xu, Y., Roy-Chowdhury, A.: Integrating motion, illumination, and structure in video sequences with applications in illumination-invariant tracking. IEEE Trans. Pattern Anal. Mach. Intell. 29, 793–806 (2007)

    Article  Google Scholar 

  12. Yang, F., Lu, H., Zhang, W., Yang, G.: Visual tracking via bag of features. IET Image Process. 6, 115–128 (2012)

    Article  MathSciNet  Google Scholar 

  13. Freedman, D., Turek, W.: Illumination-invariant tracking via graph cuts. In: IEEE Proceedings of CVPR (2005)

    Google Scholar 

  14. Mckenna, S., Raja, Y., Gong, S.: Object tracking using adaptive colour mixture models. In: Asian Conference on Computer Vision, pp. 615–622 (1998)

    Google Scholar 

  15. Bales, M., Ryan, F.: Bigbackground-based illumination compensation for surveillance video. Image Video Processing (2011). Hindawi Proceedings

    Google Scholar 

  16. Rautaray, S., Agrawal, A.: A real time hand tracking system for interactive applications. Int. J. Comput. Appl. 18, 28–33 (2011)

    Google Scholar 

  17. Huang, K., Wang, L., Tan, T., Maybank, S.: A real-time object detecting and tracking system for outdoor night surveillance. Pattern Recogn. 41, 432–444 (2008). Sciencedirect Proceedings

    Article  Google Scholar 

  18. Ning, J., Zhang, L., Zhang, D., Wu, C.: Robust mean-shift tracking with corrected background-weighted histogram. IET Comput. Vis. 6, 62–69 (2012)

    Article  MathSciNet  Google Scholar 

  19. Miller, A., Basharat, A., White, B., Liu, J., Shah, M.: Person and vehicle tracking in surveillance video. In: Stiefelhagen, R., Bowers, R., Fiscus, J. (eds.) CLEAR/RT -2007. LNCS, vol. 4625, pp. 174–178. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-68585-2_14

    Chapter  Google Scholar 

  20. Phadke, G., Velmurgan, R.: Illumination invariant mean-shift tracking. In: IEEE Workshop on Applications of Computer Vision (WACV) (2013)

    Google Scholar 

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Acknowledgment

We would like to thanks Mumbai university and Ramrao Adik Institute of Technology, Nerul for Financial support.

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Authors and Affiliations

  1. Ramrao Adik Institute of Technology, DY Patil Vidyanagari, Nerul, Navi Mumbai, India

    Shantanu Rane, Pranav Rane, Kiran Panchal & Gargi Phadke

Authors
  1. Shantanu Rane
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  2. Pranav Rane
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  3. Kiran Panchal
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  4. Gargi Phadke
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Corresponding author

Correspondence to Gargi Phadke .

Editor information

Editors and Affiliations

  1. SKNCOE, Pune, Maharashtra, India

    A.V. Deshpande

  2. Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam, India

    Aynur Unal

  3. Department of Mathematics and Computer Science, Laurentian University, Sudbury, Ontario, Canada

    Kalpdrum Passi

  4. Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh

  5. IT Buzz Limited, Dagenham, United Kingdom

    Malaya Nayak

  6. Yudiz Solutions, Ahmedabad, India

    Bharat Patel

  7. Sinhgad Group of Institutions, Pune, India

    Shafi Pathan

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Rane, S., Rane, P., Panchal, K., Phadke, G. (2018). Real Time Surveillance and Object Tracking. In: Deshpande, A., et al. Smart Trends in Information Technology and Computer Communications. SmartCom 2017. Communications in Computer and Information Science, vol 876. Springer, Singapore. https://doi.org/10.1007/978-981-13-1423-0_15

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  • DOI: https://doi.org/10.1007/978-981-13-1423-0_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1422-3

  • Online ISBN: 978-981-13-1423-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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