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2015
Conference Paper
Titel
Comparison of spatial models for foreground-background segmentation in underwater videos
Abstract
The low-level task of foreground-background segregation is an important foundation for many high-level computer vision tasks and has been intensively researched in the past. Nonetheless, unregulated environments usually impose challenging problems, especially the difficult and often neglected underwater environment. There, among others, the edges are blurred, the contrast is impaired and the colors attenuated. Our approach to this problem uses an efficient Background Subtraction algorithm and evaluates it in combination with different spatial models.