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» A Probabilistic Background Model for Tracking
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ICRA
2003
IEEE
169views Robotics» more  ICRA 2003»
14 years 26 days ago
Robust model-based 3D object recognition by combining feature matching with tracking
− We propose a vision based 3D object recognition and tracking system, which provides high level scene descriptions such as object identification and 3D pose information. The sys...
Sungho Kim, In-So Kweon, Incheol Kim
ICCV
2003
IEEE
14 years 9 months ago
Background Modeling and Subtraction of Dynamic Scenes
Background modeling and subtraction is a core component in motion analysis. The central idea behind such module is to create a probabilistic representation of the static scene tha...
Antoine Monnet, Anurag Mittal, Nikos Paragios, Vis...
AVSS
2006
IEEE
13 years 11 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
MVA
2002
195views Computer Vision» more  MVA 2002»
13 years 7 months ago
Improved Adaptive Mixture Learning for Robust Video Background Modeling
2 Related Works Gaussian mixtures are often used for data modeling in many real-time applications such as video background modeling and speaker direction tracking. The real-time a...
Dar-Shyang Lee
ICPR
2010
IEEE
14 years 2 months ago
Integrating a Discrete Motion Model into GMM Based Background Subtraction
GMM based algorithms have become the de facto standard for background subtraction in video sequences, mainly because of their ability to track multiple background distributions, w...
Christian Wolf, Jolion Jolion