Moving Object Detection and Tracking Algorithm Based on Background Subtraction

Abstract:

Moving target detection and tracking algorithm as the core issue of computer vision and human-computer interaction is the first step of intelligent video surveillance system. Through comparing temporal difference method and background subtraction, a moving object detection and tracking algorithm based on background subtraction under static background is proposed, in order to quickly and accurately detect and identify the moving object in the intelligent monitoring system. In this algorithm, firstly, we use background acquisition method to receive the background image, then use the current frame image and the received background image to perform background subtraction in order to extract foreground object information and receive the difference image; secondly, we use threshold segmentation and morphology image processing to process the difference image in order to eliminate noises and receive the clear binary moving object image; finally, we use the centroid tracking method to track and mark the moving object. Experimental results show that the algorithm can effectively and quickly detect and track moving object from video sequence under static background. This algorithm is easily realized and has good real-time and robust, which is automated and self triggered for background updating. The algorithm can be used in driver assistance systems, motion capture, virtual reality and other fields.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2211-2216
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2211
• Online since: December 2012
• Authors: Qing Ye, Yong Mei Zhang
• Keywords: Background Subtraction, Centroid Tracking, Image Preprocessing, Moving Object Detection and Tracking

References

[1] STAUFFER C, GRIMSON W E L: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.22, No.8(2000), p.747

[2] Houari Sabirin, Munchurl Kim: IEEE TRANSACTIONS ON MULTIMEDIA, Vol. 14, No. 3(2012),p.657

[3] O.Rostamianfar,F.Janabi-Sharifi,I.Hassanzadeh: Canadian Conference on Electrical and Computer Engineering( 2006),p.(2000)

DOI: 10.1109/ccece.2006.277838

[4] Wei Shui gen,Chen Zhen,Dong Hua: Second International symposium on Electronic Connerce and Security, Vol.2, (2009),p.85.

[5] Heikkila M, Pietikaninen M: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.28,No.4(2006),p.657

[6] Wei Di, Rongben Wang: International conference on Computational Intelligence and Software engineering (2009), p.1

[7] Wilson, S.S: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.14, No.6, 1992, p.636

[8] Nascimento J.C,Abrantes A.J,Marques J.S: IEEE International Conference on Acoustics,Speech, and Signal Processing,Vol.6(1999), p.3305