KEYWORDS: Visualization, Image retrieval, RGB color model, Content based image retrieval, Information visualization, Human-machine interfaces, Visual process modeling, Feature extraction, Data modeling, Databases
Is query by visual example an intuitive method for visual query formulation or merely a prototype framework for visual information retrieval research that cannot support the rich variety of visual search strategies required for effective image retrieval? This paper reports the results of an investigation that aimed to explore the usability of the query by paint method in supporting a range of information problems. While the results show that there was no significant difference, p>0.001, on all four measures of usability, query by paint was considered by this sample not to support visual query expression. It was also observed that the usability of the query method combined with the mental model of the information problem affected both visual query expression and retrieval results. This has important implications for the efficacy and utility of content-based image retrieval as a whole and there is an increasing need to examine the usefulness of query methods and retrieval features in context.
This paper reports the results of a usability experiment that investigated visual query formulation on three dimensions: effectiveness, efficiency, and user satisfaction. Twenty eight evaluation sessions were conducted in order to assess the extent to which query by visual example supports visual query formulation in a content-based image retrieval environment. In order to provide a context and focus for the investigation, the study was segmented by image type, user group, and use function. The image type consisted of a set of abstract geometric device marks supplied by the UK Trademark Registry. Users were selected from the 14 UK Patent Information Network offices. The use function was limited to the retrieval of images by shape similarity. Two client interfaces were developed for comparison purposes: Trademark Image Browser Engine (TRIBE) and Shape Query Image Retrieval Systems Engine (SQUIRE).
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