Publication
Improving background subtraction based on a casuistry of colour-motion segmentation problems
Conference Article
Conference
Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)
Edition
3rd
Pages
475-482
Doc link
http://dx.doi.org/10.1007/978-3-540-72849-8_60
File
Authors
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Huerta Casado, Ivan
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Rowe, Daniel
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Mozerov, Mikhail
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Gonzàlez Sabaté, Jordi
Projects associated
Abstract
The basis for the high-level interpretation of observed patterns of human motion still relies on motion segmentation. Popular approaches based on background subtraction use colour information to model each pixel during a training period. Nevertheless, a deep analysis on colour segmentation problems demonstrates that colour segmentation is not enough to detect all foreground objects in the image, for instance when there is a lack of colour necessary to build the background model. In this paper, our segmentation procedure is based not only on colour, but also on intensity information. Consequently, the intensity model enhances segmentation when the use of colour is not feasible. Experimental results demonstrate the feasibility of our approach.
Categories
computer vision.
Scientific reference
I. Huerta, D. Rowe, M. Mozerov and J. Gonzàlez. Improving background subtraction based on a casuistry of colour-motion segmentation problems, 3rd Iberian Conference on Pattern Recognition and Image Analysis, 2007, Girona, in Pattern Recognition and Image Analysis, Vol 4477 of Lecture Notes in Computer Science, pp. 475-482, 2007, Springer Verlag, Berlin, Alemanya.
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