Journal
SENSORS
Volume 10, Issue 2, Pages 1041-1061Publisher
MDPI
DOI: 10.3390/s100201041
Keywords
motion detector; background subtraction; iterative subdivision; region-based; histograms; Gaussian Mixture
Funding
- Fonds Quebecois de la Recherche sur la Nature et les Technologies (FQRNT)
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Canada Foundation for Innovation (CFI)
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This paper presents a region-based method for background subtraction. It relies on color histograms, texture information, and successive division of candidate rectangular image regions to model the background and detect motion. Our proposed algorithm uses this principle and combines it with Gaussian Mixture background modeling to produce a new method which outperforms the classic Gaussian Mixture background subtraction method. Our method has the advantages of filtering noise during image differentiation and providing a selectable level of detail for the contour of the moving shapes. The algorithm is tested on various video sequences and is shown to outperform state-of-the-art background subtraction methods.
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