International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Understanding and Using Context
Personal and Ubiquitous Computing
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Towards Robust Multi-cue Integration for Visual Tracking
ICVS '01 Proceedings of the Second International Workshop on Computer Vision Systems
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
An Introduction to the Kalman Filter
An Introduction to the Kalman Filter
Robust Real-Time Face Detection
International Journal of Computer Vision
Sparse Bayesian Learning for Efficient Visual Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Democratic Integration: Self-Organized Integration of Adaptive Cues
Neural Computation
Real time hand tracking by combining particle filtering and mean shift
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Scatter search particle filter for 2d real-time hands and face tracking
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
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Particle filtering is one of the most successful approaches for visual tracking. However, so far, most particle-filter trackers are limited to a single cue. This can be a serious limitation, since it can reduce the tracker’s robustness. In the current work, we present a multiple cue integration approach applied for face tracking, based on color and geometric properties. We tested it over several video sequences and we show it is very robust against changes in face appearance, scale and pose. Moreover, our technique is proposed as a contextual information for human presence detection.