Solving for Colour Constancy using a Constrained Dichromatic Reflection Model
International Journal of Computer Vision
Is Machine Colour Constancy Good Enough?
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Towards Robust Multi-cue Integration for Visual Tracking
ICVS '01 Proceedings of the Second International Workshop on Computer Vision Systems
Skin-Color Modeling and Adaptation
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume II
Multi-Modal Tracking of Faces for Video Communications
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Estimation of the Illuminant Color from Human Skin Color
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Self-Organized Integration of Adaptive Visual Cues for Face Tracking
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Skin Detection in Video under Changing Illumination Conditions
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
A survey of skin-color modeling and detection methods
Pattern Recognition
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Pearson-based mixture model for color object tracking
Machine Vision and Applications
Face detection using an adaptive skin-color filter and FMM neural networks
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
A weighted FMM neural network and its application to face detection
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
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New human computer interfaces are using computer vision systems to track faces and hands. A critical task in such systems is the segmentation. An often used approach is colour based segmentation, approximating the skin chromaticities with a statistical model, e.g. with mean value and covariance matrix. The advantage of this approach is that it is invariant to size and orientation and fast to compute. A disadvantage is that it is sensitive to changes of the illumination, and in particular to changes in the illumination colour.This paper investigates (1) how accurately the covariance matrix of skin chromaticities might be modelled for different illumination colours using a physics-based approach, (2) how this may be used as a feature to classify between skin and other materials. Results are presented using real image data taken under different illumination colours and from subjects with different shades of skin. The eigenvectors of the modelled and measured covariances deviate in orientation about 4°. The feature to distinguish skin from other surfaces is tested on sequences with changing illumination conditions containing hands and other materials. In most cases it is possible to distinguish between skin and other objects.