Name
Abstract | ||
|---|---|---|
Background estimation is one of the most challenging phases in extracting foreground objects from video sequences. In this paper we present a background modeling approach that uses the similarity of frames to extract background areas from the video sequence. We use a window over the frames history and compute the similarity between the selected frames of this window as a similarity window. The properties of similarity window depend on the characteristics of the scene and can be adjusted parametrically. Our primary results show that if proper parameters are chosen, this method can give a good approximation of the background model. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/AICCSA.2008.4493595 | AICCSA |
Keywords | Field | DocType |
similarity window,background modeling approach,background estimation approach,frames history,challenging phase,background area,foreground object,background estimation,good approximation,background model,video sequence,image processing | Background subtraction,Computer vision,Pattern recognition,Computer science,Image processing,Artificial intelligence | Conference |
ISSN | ISBN | Citations |
2161-5322 | 978-1-4244-1968-5 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ehsan Shahrian | 1 | 53 | 2.07 |
| Hossein Karshenas | 2 | 147 | 7.79 |
| Mahmood Fathy | 3 | 482 | 63.71 |