DocumentCode
554163
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
Volume
3
fYear
2011
fDate
26-28 July 2011
Firstpage
1607
Lastpage
1610
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022376
Filename
6022376
Link To Document