Robust multiple car tracking with occlusion reasoning
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Statistical background modelling for tracking with a virtual camera
BMVC '95 Proceedings of the 6th British conference on Machine vision (Vol. 2)
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A Real-time Computer Vision System for Measuring Traffic Parameters
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Object Localization by Bayesian Correlation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability)
Automatic Detection and Tracking of Human Motion with a View-Based Representation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Background Segmentation Using Spatial-Temporal Multi-Resolution MRF
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Background Subtraction Using Markov Thresholds
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Vs-star: A visual interpretation system for visual surveillance
Pattern Recognition Letters
Light-weight salient foreground detection for embedded smart cameras
Computer Vision and Image Understanding
Joint random field model for all-weather moving vehicle detection
IEEE Transactions on Image Processing
Switching observation models for contour tracking in clutter
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Markovian framework for foreground-background-shadow separation of real world video scenes
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
A survey of techniques for incremental learning of HMM parameters
Information Sciences: an International Journal
Journal of Signal Processing Systems
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A new probabilistic background model based on a Hidden Markov Model is presented. The hidden states of the model enable discrimination between foreground, background and shadow. This model functions as a low level process for a car tracker. A particle filter is employed as a stochastic filter for the car tracker. The use of a particle filter allows the incorporation of the information from the low level process via importance sampling. A novel observation density for the particle filter which models the statistical dependence of neighboring pixels based on a Markov random field is presented. The effectiveness of both the low level process and the observation likelihood are demonstrated.