Spatially correlated background subtraction, based on adaptive background maintenance
Journal of Visual Communication and Image Representation
Robust detection of moving objects in video sequences through rough set theory framework
Image and Vision Computing
Background subtraction with dirichlet processes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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Moving object detection is a critical task for many computer vision applications: the objective is the classification of the pixels in the video sequence into either foreground or background. A commonly used technique to achieve it in scenes captured by a static camera is Background Subtraction (BGS). Several BGS techniques have been proposed in the literature but a rigorous comparison that analyzes the different parameter configuration for each technique in different scenarios with precise ground-truth data is still lacking. In this sense, we have implemented and evaluated the most relevant BGS techniques, and performed a quantitative and qualitative comparison between them.