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» A Probabilistic Background Model for Tracking
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PRICAI
2004
Springer
15 years 5 months ago
Adaptive Model for Foreground Extraction in Adverse Lighting Conditions
Background elimination models are widely used in motion tracking systems. Our aim is to develop a system that performs reliably under adverse lighting conditions. In particular, th...
Stewart Greenhill, Svetha Venkatesh, Geoff A. W. W...
BMVC
1998
15 years 1 months ago
Learning Enhanced 3D Models for Vehicle Tracking
This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic obj...
James M. Ferryman, Anthony D. Worrall, Stephen J. ...
ICCV
2009
IEEE
14 years 9 months ago
Segmentation, ordering and multi-object tracking using graphical models
In this paper, we propose a unified graphical-model framework to interpret a scene composed of multiple objects in monocular video sequences. Using a single pairwise Markov random...
Chaohui Wang, Martin de La Gorce, Nikos Paragios
IBPRIA
2009
Springer
14 years 9 months ago
Real-Time Motion Detection for a Mobile Observer Using Multiple Kernel Tracking and Belief Propagation
We propose a novel statistical method for motion detection and background maintenance for a mobile observer. Our method is based on global motion estimation and statistical backgro...
Marc Vivet, Brais Martínez, Xavier Binefa
CAIP
2003
Springer
176views Image Analysis» more  CAIP 2003»
15 years 5 months ago
Evaluation of an Adaptive Composite Gaussian Model in Video Surveillance
Video surveillance systems seek to automatically identify events of interest in a variety of situations. Extracting a moving object from background is the most important step of t...
Qi Zang, Reinhard Klette