Share Email Print
cover

Proceedings Paper

Moving target detection algorithm based on Gaussian mixture model
Author(s): Zhihua Wang; Du Kai; Xiandong Zhang
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In real-time video surveillance system, background noise and disturbance for the detection of moving objects will have a significant impact. The traditional Gaussian mixture model(GMM)has strong adaptive various complex background ability, but slow convergence speed and vulnerable to illumination change influence. the paper proposes an improved moving target detection algorithm based on Gaussian mixture model which increase the convergence rate of foreground to the background model transformation and introducing the concept of the changing factors, through the three frame differential method solved light mutation problem. The results show that this algorithm can improve the accuracy of the moving object detection, and has good stability and real-time.

Paper Details

Date Published: 19 July 2013
PDF: 5 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88782O (19 July 2013); doi: 10.1117/12.2030634
Show Author Affiliations
Zhihua Wang, Chongqing Univ. of Technology (China)
Du Kai, Chongqing Univ. of Technology (China)
Xiandong Zhang, Chongqing Univ. of Technology (China)


Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

© SPIE. Terms of Use
Back to Top