Title :
A novel algorithm of adaptive background estimation
Author :
Gao, Da-shan ; Zhou, Jie ; Xin, Le-ping
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
We propose an adaptive background estimation algorithm for an outdoor video surveillance system. In order to enhance the ability of adaptation to illumination changes and variant noise in long-term running, an improved Kalman filtering model based on the local-region is discussed to dynamically estimate a background image, in which the parameters are predicted by a recursive-least-square adaptive filter. The experimental results on real-world video show that the algorithm can perform robustly and effectively
Keywords :
Kalman filters; adaptive estimation; adaptive filters; image enhancement; least squares approximations; recursive estimation; recursive filters; statistical analysis; surveillance; video signal processing; Kalman filtering model; RLS filter; adaptive background estimation algorithm; adaptive filter; background image; dynamic estimation; illumination changes; image enhancement; image histogram; local region; outdoor video surveillance system; parameter prediction; real-time traffic monitoring; recursive-least-square filter; variant noise; Adaptive filters; Background noise; Change detection algorithms; Filtering; Kalman filters; Lighting; Pixel; Recursive estimation; Vehicle detection; Video surveillance;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.958511
