Segmentation of Moving Object in Video Surveillance using Optical Drift

Authors

  • Ms.Thakare Mitali Author
  • Mrs. J.H.Patil Author

Keywords:

Lucas Kanade method, Motion vector Optical flow estimation, SAD ,Video segmentation.

Abstract

With the abrupt increase of motor vehicles, the advanced Intelligent Traffic Monitoring System is important in today's world. Automatic video segmentation plays an important role in the ITMS. Many algorithms have been proposed on automatic video segmentation. However, due to the large computation, many of them can-not be used for the real-time applications. Segmentation of moving objects in a scene is often desired in many applications for monitoring motion. In the project, we look at traffic videos. The approach used for object-oriented video segmentation is based on motion coherence.

References

[1] Shaoguo Liu, Haibo Wang, Jue Wang and Chunhong Pan, “Blur-Kernel Bound Estimation from Pyramid Statistics”, IEEE TRANSACTIONS CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY LETTERS 2015.

[2] Pascal Zille, Thomas Corpetti, Liang Shao, and Xu Chen, “Model Based on Scale Interactions for Optical Flow Estimation”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 23, NO. 8, AUGUST 2014.

[3] SukHwan Lim, Member, IEEE, John G. Apostolopoulos, Member, IEEE, “Optical Flow Estimation Temporally Oversampled Video”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 14, NO. 8, AUGUST 2005.

[4] X. Wu, C.-W. Ngo, A. Hauptmann, and H.-K. Tan, “Real-Time Near-Duplicate Elimination for Web Video Search with Content and Context,” IEEE Trans. Multimedia, vol. 11, no. 2, pp. 196-207, Feb. 2009.

[5] K. Kanatani, “Motion segmentation by subspace separation and model.

[6] Simon Lucey, Member, IEEE, Rajitha Navarathna, Student Member, IEEE, Ahmed Bilal Ashraf, and Sridha Sridharan, Senior Member, IEEE , “Fourier Lucas-Kanade Algorithm”, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 35, NO. 6, JUNE 2013.

[7] Han-Soo Seong, Chae Eun Rhee, and Hyuk-Jae Lee, “A Novel Hardware Architecture of the Lucas-Kanade Optical Flow for Reduced Frame Memory Access”, Transactions on Circuits and Systems for Video Technology 2015 IEEE.

[8] Synh Viet Uyen Ha, Xuan Dai Pham and Jae Wook Jeon, Member, IEEE, “Improving Estimation of High Accuracy Optical Flow by Unstable Region Detection “, Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems Seoul, Korea, August 20 - 22, 2008

[9] M. Mueller, P. Karasev, I. Kolesov and A. Tannenbaum, "Optical Flow Estimation for Flame Detection in Videos," in IEEE Transactions on Image Processing, vol. 22, no. 7, pp. 2786-2797, July 2013.

[10] W.S.P. Fernando, Lanka Udawatta, “Identification of Moving Obstacles with Pyramidal Lucas Kanade Optical Flow and k means Clustering”, 2007 IEEEAkanksha Vyas, Manish Sharma, Fuzzy based sleep scheduling in TDM Passive Optical Network, Fourth International Conference on Communication Systems and Network Technologies, 2014.

Downloads

Published

2017-06-30

How to Cite

Segmentation of Moving Object in Video Surveillance using Optical Drift. (2017). International Journal of Advanced Research in Science, Management and Technology, 3(3), 1-6. https://ijarsmt.in/ijarsmt/article/view/51

Most read articles by the same author(s)

Similar Articles

31-40 of 44

You may also start an advanced similarity search for this article.