Probabilistic and Voting Approaches to Cue Integration for Figure-Ground Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Real-Time Face Tracking under Partial Occlusion and Illumination Change
ICMI '00 Proceedings of the Third International Conference on Advances in Multimodal Interfaces
Towards Robust Multi-cue Integration for Visual Tracking
ICVS '01 Proceedings of the Second International Workshop on Computer Vision Systems
Towards Robust Perception and Model Integration
Revised Papers from the International Workshop on Sensor Based Intelligent Robots
Machine Vision and Applications - Special issue: IEEE WACV
Tracking regions of human skin through illumination changes
Pattern Recognition Letters - Special issue: Colour image processing and analysis
Democratic Integration: Self-Organized Integration of Adaptive Cues
Neural Computation
A General Framework for Combining Visual Trackers --- The "Black Boxes" Approach
International Journal of Computer Vision
MAP ZDF segmentation and tracking using active stereo vision: Hand tracking case study
Computer Vision and Image Understanding
A novel face and hands tracking in a complex background
CIMMACS'06 Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics
Figure-ground separation by cue integration
Neural Computation
Robust human tracking based on multi-cue integration and mean-shift
Pattern Recognition Letters
Foundations and Trends in Robotics
A probabilistic framework for combining tracking algorithms
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
An offline bidirectional tracking scheme
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Dynamic appearance model for particle filter based visual tracking
Pattern Recognition
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A mechanism for the self-organized integration of different adaptive cues is proposed. In Democratic Integration the cues agree on a result and each cue adapts towards the result agreed upon. A technical formulation of this scheme is employed in a face tracking system. The self-organized adaptivity leads to suppression and recalibration of discordant cues. Experiments show that the system is robust to sudden changes in the environment as long as the changes disrupt only a minority of cues at the same time, although all cues may be affected in the long run.