Robust multiple car tracking with occlusion reasoning
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Probabilistic Background Model for Tracking
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Constructing free-energy approximations and generalized belief propagation algorithms
IEEE Transactions on Information Theory
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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 background modeling. In order to estimate the global motion, we use a Multiple Kernel Tracking combined with an adaptable model, formed by weighted histograms. This method is very light in terms of computation time and also in memory requirements, enabling the use of other methods more expensive, like belief propagation, to improve the final result.