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Abstract: Background modeling is an important component of many vision systems. Existing work in the area has mostly addressed scenes that consist of static or quasi-static structures. When the scene exhibits a persistent dynamic behavior in time, such an assumption is violated and detection performance deteriorates. In this paper, we propose a new method for the modeling and subtraction of such scenes. Towards the modeling of the dynamic characteristics, optical flow is computed and utilized as a... (Update)
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0.5: Background Modeling and Subtraction of Dynamic Scenes - Antoine Monnet Anurag (2003) (Correct)
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BibTeX entry: (Update)
A. Mittal and N. Paragios. Motion-based background subtraction using adaptive kernel density estimation. Computer Vision and Pattern Recognition, June 2000. http://citeseer.ist.psu.edu/mittal04motionbased.html More
@misc{ mittal00motionbased,
author = "A. Mittal and N. Paragios",
title = "Motion-based background subtraction using adaptive kernel density estimation",
text = "A. Mittal and N. Paragios. Motion-based background subtraction using adaptive
kernel density estimation. Computer Vision and Pattern Recognition, June
2000.",
year = "2000",
url = "citeseer.ist.psu.edu/mittal04motionbased.html" }
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