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» A Probabilistic Background Model for Tracking
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98
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CVPR
2004
IEEE
15 years 11 months ago
An Algorithm for Multiple Object Trajectory Tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state a...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
ACCV
2010
Springer
14 years 4 months ago
MRF-Based Background Initialisation for Improved Foreground Detection in Cluttered Surveillance Videos
Abstract. Robust foreground object segmentation via background modelling is a difficult problem in cluttered environments, where obtaining a clear view of the background to model i...
Vikas Reddy, Conrad Sanderson, Andres Sanin, Brian...
ACCV
2006
Springer
15 years 3 months ago
A Novel Robust Statistical Method for Background Initialization and Visual Surveillance
In many visual tracking and surveillance systems, it is important to initialize a background model using a training video sequence which may include foreground objects. In such a c...
Hanzi Wang, David Suter
85
Voted
ECCV
2004
Springer
15 years 11 months ago
Audio-Video Integration for Background Modelling
This paper introduces a new concept of surveillance, namely, audio-visual data integration for background modelling. Actually, visual data acquired by a fixed camera can be easily ...
Marco Cristani, Manuele Bicego, Vittorio Murino
ECCV
2004
Springer
15 years 11 months ago
Adaptive Probabilistic Visual Tracking with Incremental Subspace Update
Visual tracking, in essence, deals with non-stationary data streams that change over time. While most existing algorithms are able to track objects well in controlled environments,...
David A. Ross, Jongwoo Lim, Ming-Hsuan Yang