Color models for outdoor machine vision
Computer Vision and Image Understanding
Recognizing Objects Using Color-Annotated Adjacency Graphs
Shape, Contour and Grouping in Computer Vision
Skin Patch Detection in Real-World Images
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Camera-based colour sensing system
EHAC'06 Proceedings of the 5th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications
A sequential Bayesian approach to color constancy using non-uniform filters
Computer Vision and Image Understanding
Learning-based robot vision: principles and applications
Learning-based robot vision: principles and applications
Distributed tracking in a large-scale network of smart cameras
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
A robust illumination estimate for chromatic adaptation in rendered images
EGSR'09 Proceedings of the Twentieth Eurographics conference on Rendering
A linear system form solution to compute the local space average color
Machine Vision and Applications
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Illumination is rarely constant in intensity or color throughout a scene. Multiple light sources with different spectra-sun and sky, direct and interreflected light-are the norm. Nonetheless, almost all color constancy algorithms assume that the spectrum of the incident illumination remains constant across the scene. We assume the converse, that illumination does vary, in developing a new algorithm for color constancy. Rather than creating difficulties, varying illumination is in fact a very powerful constraint. Indeed tests of our algorithm using real images of an office scene show excellent results.