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Dynamic Control of Adaptive Mixture-of-Gaussians Background Model
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A Framework for High-Level Feedback to Adaptive, Per-Pixel, Mixture-of-Gaussian Background Models
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Online Adaptive Gaussian Mixture Learning for Video Applications
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Adaptive background mixture models for real-time tracking
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Wallflower: principles and practice of background maintenance
inferredcites →https://doi.org/10.1109/icip.2003.1247409openalex-snapshot
A Bayesian framework for Gaussian mixture background modeling
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Background and foreground modeling using nonparametric kernel density estimation for visual surveillance
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Illumination normalization with time-dependent intrinsic images for video surveillance
inferredcites →https://doi.org/10.1109/tpami.2005.102openalex-snapshot
Effective Gaussian mixture learning for video background subtraction
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Approche pixel de la soustraction d'arrière-plan en vidéo, basée sur un mélange de gaussiennes imprécises
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