Human Vision System's Region of Interest Based Video Coding

Authors

  • Asha K. UG Scholar, IT Department, P.S.V. College of Engineering and Technology, Krishnagiri, India.
  • Anuradha D UG Scholar, IT Department, P.S.V. College of Engineering and Technology, Krishnagiri, India.
  • Saravanan V Assistant Professor, IT Department, P.S.V. College of Engineering and Technology, Krishnagiri, India
  • Rizvana M. Assistant Professor, IT Department, P.S.V. College of Engineering and Technology, Krishnagiri, India

Keywords:

Video Compression, Human Vision System, Background, Foreground, Spatial, Temporal

Abstract

While watching a video human visual system gives more attention on the foreground objects than background objects. That is to say, human vision system pays more attention to region of interest, such as the human faces in the video content. Most of the video encoders compress video by considering every part of the video frames with equal importance. So the video size could not be Video Compressionreduced to maintain quality. The proposed system can detect the foreground and it can allocate different bit rates for different regions. By doing this the video quality can be maintained and the size can be reduced up to 40%.

References

. Y.-F.Ma and H.-J. Zhang, “A model of motion attention for video skimming,” in Proc. ICIP, vol. 1, Sept. 2002, pp. I-129–I-132.

. Y. Takahashi, N. Nitta, and N. Babaguchi, “Video summarization for large sports video archives,” in Proceedings of the IEEE International Conference on Multimedia and Expo (ICME ’05), pp. 1170–1173, Amsterdam, The Netherlands, July 2005.

. Y.-F. Ma, L. Lu, H.-J. Zhang, and M. Li, “A user attention model for video summarization,” in Proceedings of the 10th ACM International Multimedia Conference and Exhibition, pp. 533–542, Juan Les Pins, France, December 2002.

. H.J Zhang, et al, “An integrated system for content-based video retrieval and browsing,” Pattern Recognition, vol.30, no.4, pp.643-658, 1997.

. C. Kim and J. N. Hwang, “An integrated scheme for objectbased video abstraction,” Proc. Of ACM Multimedia 2000. Los Angeles, CA, 2000.

. S. Z. Li, et al., “Statistical Learning of Multi-View Face Detection,” Proc. of ECCV 2002.

. Y. Tian, Max Lu, and A. Hampapur, “Robust and Efficient Foreground Analysis for Realtime Video Surveillance,” IEEE CVPR, San Diego. June, 2005.

. S. Cheung and C. Kamath, “Robust background subtraction with foreground validation for urban traffic video”, EURASIP Journal of Applied Signal Processing, Special Issue on Advances in Intelligent Vision Systems, 2005.

. V.Saravanan, Dr.A.Sumathi, S.Shanthana and M.Rizvana, “Dual Mode Mpeg Steganography Scheme For Mobile and Fixed Devices”, International Journal of Engineering Research and Development, Volume 6, Issue 3 PP. 23-27, Mar 2013.

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Published

2024-02-26

How to Cite

Asha, K., Anuradha, D., Saravanan, V., & Rizvana, M. (2024). Human Vision System’s Region of Interest Based Video Coding. COMPUSOFT: An International Journal of Advanced Computer Technology, 2(05), 127–129. Retrieved from https://ijact.in/index.php/j/article/view/24

Issue

Vol. 2 No. 05 (2013): May

Section

Original Research Article

License

Copyright (c) 2013 COMPUSOFT: An International Journal of Advanced Computer Technology

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