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Reseach Article

Detecting and Tracking of Moving Objects from Video

by Tushar S. Waykole, Yogendra Kumar Jain
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 18
Year of Publication: 2013
Authors: Tushar S. Waykole, Yogendra Kumar Jain
10.5120/14224-2410

Tushar S. Waykole, Yogendra Kumar Jain . Detecting and Tracking of Moving Objects from Video. International Journal of Computer Applications. 81, 18 ( November 2013), 23-28. DOI=10.5120/14224-2410

@article{ 10.5120/14224-2410,
author = { Tushar S. Waykole, Yogendra Kumar Jain },
title = { Detecting and Tracking of Moving Objects from Video },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 18 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 23-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number18/14224-2410/ },
doi = { 10.5120/14224-2410 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:34.189825+05:30
%A Tushar S. Waykole
%A Yogendra Kumar Jain
%T Detecting and Tracking of Moving Objects from Video
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 18
%P 23-28
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Background Subtraction methods are widely used for detecting and tracking moving objects in videos. It is useful in many applications such as traffic monitoring, video surveillances. The accurate tracking and detection of moving object is the challenging aspect of such approach. This work proposes a general purpose method which combines the advantage of spatio-temporal differencing with the basic background subtraction method. The results are promising on the proposed method as compared with the basic model of background subtraction and mean shift method.

References
  1. Shireen Y. Elhabian, Khaled M. El-Sayed and Sumaya H. Ahmed, "Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art" , 2008, Recent Patents on Computer Science, Vol. 1, No.
  2. R. C. Gonzalez and R. E. Woods. , "Digital Image Processing", Prentice Hall, 2002.
  3. Jacinto Nascimento, Jorge Marques," Performance evaluation of object detection algorithms for video surveillance", Project CAVIAR, 2001
  4. Kinjal A Joshi, Darshak G. Thakore, "A Survey on Moving Object Detection and Tracking in Video Surveillance System", July 2012,International Journal of Soft Computing and Engineering (IJSCE), Volume-2, Issue-3
  5. I. Haritaoglu, D. Harwood, and L. S. Davis, "W4: real-time surveillance of people and their activities," IEEE Trans. Pattern Anal. Machine Intell. , vol. 22, no. 8, pp. 809–830, August 2000.
  6. Shan, C. , Tan, T. , Wei, Y. , "Real-time hand tracking using a mean shift embedded particle filter", Pattern Recognition, Vol. 40, No. 7, pp. 1958-1970, 2007.
  7. Bahadir Karasulu, "Review And Evaluation Of Well-nown Methods For Moving Object Detection And Tracking In Videos", July 2010, Journal of Aeronautics and Space Technologies
  8. Jodoin, P. M. , Mignotte, M. , "Optical-flow based on an edge-avoidance procedure", Computer Vision and Image Understanding, Vol. 113, No. 4, pp. 511-531, 2009.
  9. Dagher, I. , Tom, K. E. , "WaterBalloons: A hybrid watershed Balloon Snake segmentation", Image and Vision Computing, Vol. 26, pp. 905–912, doi:10. 1016/j. imavis. 2007. 10. 010, 2008.
  10. S. Y. Elhabian, K. M. El-Sayed, "Moving object detection in spatial domain using background removal techniques- state of the art", Recent patents on computer science, vol. 1, pp 32-54, Apr, 2008.
  11. Badri Narayan Subudhi, Pradipta Kumar Nanda, and Ashish Ghosh, "A Change Information Based Fast Algorithm for Video Object Detection and Tracking", , IEEE Transactions on Circuits and Systems for Video Technology, July 2011.
  12. A. Amer. "Voting-based simultaneous tracking of multiple video objects". Proc. SPIE Int. Symposium on Electronic Imaging, pages 500–511, Santa Clara, USA, January 2003.
  13. Abhishek Kumar Chauhan, Deep Kumar, "Study of Moving Object Detections and Trackings for Video Surveillance", 2013.
  14. Alper Yilmaz, Omar Javed, Mubarak Shah, "Object tracking: A survey", ACM Comput. Surv. 38, 4, Article 13,December 2006.
  15. In Su Kim, Hong Seok Choi, Kwang Moo Yi, Jin Young Choi, and Seong G. Kong, "Intelligent Visual Surveillance - A Survey" 2010, International Journal of Control, Automation, and Systems, 8(5):926-939. [
  16. Ahmed Elgammal, Ramani Duraiswami, David Darwood, and Larry S. Davis , "Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance", July 2002,Proceedings of the IEEE, vol. 90, no. 7
  17. Jong Sun Kim, Dong Hae Yeom, and Young Hoon Joo, "Fast and Robust Algorithm of Tracking Multiple Moving Objects for Intelligent Video Surveillance Systems" August 2011, IEEE Transactions on Consumer Electronics, Vol. 57, No. 3
  18. Vibha L, Chetana Hegde, P Deepa Shenoy, Venugopal K R, L M Patnaik, "Dynamic Object Detection, Tracking and Counting in Video Streams for Multimedia Mining", July 2008,IAENG International Journal of Computer Science, 35:3, IJCS 35_3_16
  19. Dorin Comaniciu and Peter Meer, "Mean Shift – A Robust Approach Toward Feature Space Analysis", May 2002, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 24, No. 5
  20. Teddy Ko (2011). A Survey on Behavior Analysis in Video Surveillance Applications, Video Surveillance, Prof. Weiyao Lin (Ed. ), ISBN: 978-953-307-436-8, InTech.
  21. P. Spagnolo, T. D' Orazio, M. Leo, A. Distante, "Moving object segmentation by background subtraction and temporal analysis", Image and Vision Computing 24 (2006).
Index Terms

Computer Science
Information Sciences

Keywords

Background subtraction Spatio-temporal differencing Mean shift