Mathematics of Data Fusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental Learning for Robust Visual Tracking
International Journal of Computer Vision
Segmentation and Tracking of Multiple Humans in Crowded Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating multiple object tracking performance: the CLEAR MOT metrics
Journal on Image and Video Processing - Regular
Tracking Multiple Occluding People by Localizing on Multiple Scene Planes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Occlusion reasoning for tracking multiple people
IEEE Transactions on Circuits and Systems for Video Technology
Learning scene context for multiple object tracking
IEEE Transactions on Image Processing
Kernel-Bayesian framework for object tracking
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Multiple objects tracking in the presence of long-term occlusions
Computer Vision and Image Understanding
Multi-object detection and tracking by stereo vision
Pattern Recognition
Joint detection and estimation of multiple objects from image observations
IEEE Transactions on Signal Processing
Probabilistic people tracking with appearance models and occlusion classification: The AD-HOC system
Pattern Recognition Letters
Tracking appearances with occlusions
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Correlation-based incremental visual tracking
Pattern Recognition
Robust visual tracking with structured sparse representation appearance model
Pattern Recognition
The Gaussian Mixture Probability Hypothesis Density Filter
IEEE Transactions on Signal Processing
A Game Theory Approach to Target Tracking in Sensor Networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive Object Tracking Based on an Effective Appearance Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Data-Driven Probability Hypothesis Density Filter for Visual Tracking
IEEE Transactions on Circuits and Systems for Video Technology
Efficient Multitarget Visual Tracking Using Random Finite Sets
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Multi-target visual tracking is a challenge because of data association and mutual occlusion in the interacting targets. This paper presents a Gaussian mixture probability hypothesis density based multi-target visual tracking system with game-theoretical occlusion handling. Firstly, the spatial constraint based appearance model with other interacting targets' interferences is modeled. Then, a two-step occlusion reasoning algorithm is proposed. Finally, an n-person, non-zero-sum, non-cooperative game is constructed to handle the mutual occlusion problem. The individual targets within the occlusion region are regarded as the players in the constructed game to compete for the maximum utilities by using the certain strategies. A Nash Equilibrium of the game is the optimal estimation of the locations of the players within the occlusion region. Experiments on video sequences demonstrate the good performance of the proposed occlusion handling algorithm.