Title :
An effective adaptive updating algorithm of background based on statistical and non-linear control
Author :
Ye Qing ; Sun YaoDong
Author_Institution :
Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
The background differing has been taken as a very excellent method for dealing with the tracing target, in the field of automated video surveillance application. This algorithm can detect the objective timely and accurately. At present more and more scholars take their attention in subtracting the background more faster and more precisely. In this paper, using the Kalman Filter and getting different parameters to control the background updating. To compare with the UKF model, this method can update faster and has ability to deal with the complicated environments.
Keywords :
Kalman filters; object detection; statistical analysis; video surveillance; Kalman filter; adaptive updating algorithm; automated video surveillance; background differing; nonlinear control; statistical control; tracing target; Computational modeling; Equations; Kalman filters; Mathematical model; Maximum likelihood detection; Nonlinear filters; Optical filters; Background Differ; Errors Analysis; Frame Differ; Kalman Filter;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022376