Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Introduction to Variational Methods for Graphical Models
Machine Learning
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Elliptical Head Tracking Using Intensity Gradients and Color Histograms
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Proceedings of the 12th annual ACM international conference on Multimedia
Accurate 3D Tracking of Rigid Objects with Occlusion Using Active Appearance Models
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Variational Maximum A Posteriori by Annealed Mean Field Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Resolving complex occlusions of objects during tracking using region based segmentations
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
Multiview-based cooperative tracking of multiple human objects
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
A New Hierarchical Particle Filter Based Tracking System for Soccer Game Analysis
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Note: Target tracking with incomplete detection
Computer Vision and Image Understanding
Occlusion reasoning for tracking multiple people
IEEE Transactions on Circuits and Systems for Video Technology
Machine Vision and Applications
On reasoning over tracking events
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
A multi-view camera system for the generation of real-time occlusion-free scene video
Proceedings of the 29th DAGM conference on Pattern recognition
Multiple objects tracking in the presence of long-term occlusions
Computer Vision and Image Understanding
Segmenting and tracking multiple objects under occlusion using multi-label graph cut
Computers and Electrical Engineering
Probabilistic people tracking with appearance models and occlusion classification: The AD-HOC system
Pattern Recognition Letters
Occlusion handling with l1-regularized sparse reconstruction
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Simulated annealing based hand tracking in a discrete space
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Multiple hypothesis target tracking using merge and split of graph’s nodes
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Target tracking under occlusion by combining integral-intensity-matching with multi-block-voting
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Game-theoretical occlusion handling for multi-target visual tracking
Pattern Recognition
Hi-index | 0.00 |
Occlusion is a difficult problem for appearance-based target tracking, especially when we need to track multiple targets simultaneously and maintain the target identities during tracking. To cope with the occlusion problem explicitly, this paper proposes a dynamic Bayesian network which accommodates an extra hidden process for occlusion and stipulates the conditions on which the image observation likelihood is calculated. The statistical inference of such a hidden process can reveal the occlusion relations among different targets, which makes the tracker more robust against partial even complete occlusions. In addition, considering the fact that target appearances change with views, another generative model for multiple view representation is proposed by adding a switching variable to select from different view templates. The integration of the occlusion model and multiple view model results in a complex dynamic Bayesian network, where extra hidden processes describe the switch of targets' templates, the targets' dynamics, and the occlusions among different targets. The tracking and inferencing algorithms are implemented by the sampling-based sequential Monte Carlo strategies. Our experiments show the effectiveness of the proposed probabilistic models and the algorithms.