Name
Abstract | ||
|---|---|---|
Background subtraction is one of the main techniques to extract moving objects from background scenes. A mixture of Gaussians is a common model for background subtraction that has been used in many applications. However modelling background pixels using this model results into a low-level process at pixel level. Some of its main drawbacks are: a subtracted (moving object) region may contain holes; it can not solve partial occlusion problems, and it requires updates in cases of shadows or sudden changes in the scene. We present a multi-layered mixture of Gaussians model named PixelMap. We combine the mixture of Gaussians model with concepts defined by region level and frame level considerations. Our experimental results show that our method improved the accuracy of extracting moving objects from background. A single stationary camera has been used. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICPR.2004.779 | ICPR (2) |
Keywords | Field | DocType |
background subtraction,pixel level,multi-layered mixture,frame level consideration,background scene,region level,common model,gaussians model,robust background subtraction,modelling background,model result,gaussian processes,feature extraction,mixture of gaussians | Background subtraction,Computer vision,Pattern recognition,Computer science,Feature extraction,Gaussian process,Artificial intelligence,Pixel,Mixture model | Conference |
ISSN | ISBN | Citations |
1051-4651 | 0-7695-2128-2 | 13 |
PageRank | References | Authors |
2.14 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qi Zang | 1 | 26 | 4.66 |
| Reinhard Klette | 2 | 1743 | 228.94 |