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 :
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