DocumentCode
1632056
Title
Spatial mixture of Gaussians for dynamic background modelling
Author
Varadarajan, Srenivas ; Miller, Paul ; Huiyu Zhou
fYear
2013
Firstpage
63
Lastpage
68
Abstract
Modelling pixels using mixture of Gaussian distributions is a popular approach for removing background in video sequences. This approach works well for static backgrounds because the pixels are assumed to be independent of each other. However, when the background is dynamic, this is not very effective. In this paper, we propose a generalisation of the algorithm where the spatial relationship between pixels is taken into account. In essence, we model regions as mixture distributions rather than individual pixels. Using experimental verification on various video sequences, we show that our method is able to model and subtract backgrounds effectively in scenes with complex dynamic textures.
Keywords
Gaussian processes; image sequences; image texture; video signal processing; Gaussian distributions; Gaussian spatial mixture; algorithm generalisation; background removal; complex dynamic textures; dynamic background modelling; mixture distributions; pixel modelling; static backgrounds; video sequences; Adaptation models; Approximation algorithms; Clustering algorithms; Dynamics; Equations; Heuristic algorithms; Mathematical model;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Video and Signal Based Surveillance (AVSS), 2013 10th IEEE International Conference on
Conference_Location
Krakow
Type
conf
DOI
10.1109/AVSS.2013.6636617
Filename
6636617
Link To Document