Colour in Context
Research group
Computer Vision Center



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The CVC colour group focuses its research in areas related to computational colour within computer vision. Our long term objective is to create computer algorithms that simulate human perception and categorisation of colour. To achieve this aim, we study colour as a visual cue in its context. Our main research lines are colour constancy, induction, saliency, texture,segmentation and naming.



Color Feature Detection for Object Recognition
Luminance edges are still the main source of information in the state-of-the-art methods for feature detection. We propose to exploit the statistical structure of luminance and color in natural images to extract the most discriminative features from the viewpoint of information theory for object recognition.
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Physics-based color image segmentation
Based on an analysis of the bi-directional reflection model we propose a method which is particularly suited for segmentation in the presence of shadow and highlight edges.
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Image Compression
The aim of this work is to apply perceptual concepts to defina a perceptual pre-quantizer in order to improve image compression algorithms.
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Color-Texture descriptors
We propose color-texture descriptors that are directly based on a perceptual theory of texture discrimination (Julesz’s Texton Theory).
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Color attention for object recognition
We propose a novel image representation where color attention is used to sample the shape description of the image.
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