Data and Model-Driven Selection using Color Regions

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Data and Model-Driven Selection using Color Regions
A key problem in model-based object recognition is selection, namely, the problem of determining which regions in the image are likely to come from a single object. In this paper we present an approach that uses color as a cue to perform selection either based solely on image-data (data-driven), or based on the knowledge of the color description of the model (model-driven). Specifically, the paper presents a method of color specification in terms of perceptual color categories and shows its relevance for the task of selection. The color categories are used to develop a fast region segmentation algorithm that extracts perceptual color regions in images. The color regions extracted form the basis for performing data and model-driven selection. Data-driven selection is achieved by selecting salient color regions as judged by a color-saliency measure that emphasizes attributes that are also important in human color perception. The approach to model-driven selection, on the other hand, expl...
Tanveer Fathima Syeda-Mahmood
Added 10 Aug 2010
Updated 10 Aug 2010
Type Conference
Year 1992
Where ECCV
Authors Tanveer Fathima Syeda-Mahmood
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