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Themesicon: navigation pathMapping and Texticon: navigation pathImage Search

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We propose to direct our tool towards the ability of performing:


• Intelligent sampling, subsets of the image collection are extracted that represent well the diversity of the original collection; • Organized visit, a coherent path is defined for the visit of the collection. The real analogy with a Museum Guide applies fully here;


• Hierarchical visit, the collection is organized in a hierarchy so as to explore interesting parts only or all parts in an interactive manner. Here again the analogy with museum rooms and wings applies; One interesting fact is that, in the above context, the basic visual characteristics show enough performance to achieve a sufficient organizational level that allows the user to keep track of the collection content. The solution here is not so much that of understanding the image (as before) but rather to capture the diversity of the collection. The above highlighted features of diversity, coherence and interest are reachable using our low-level feature set including color texture and shape. The key part of our system is the user. Within


this context, emphasis is placed back on human-machine communication, which is accepted to be one important key for development of semantic-based systems. It is now the role of designers (e.g. of interfaces) to create appropriate transfer modes of collection information onto maps such as that shown above.


Nowadays volumes of multimedia data force the use of automated tools for management. While feasibility has been proven for textual data with the development of search engines such as Google, the problem remains for visual data.

Recent research and developments have focused on a query-based context placing the user as a customer to the system. We propose the «Collection Guiding» context that shows to be more suited for several current needs but also more flexible in accommodating user requirements and interaction modalities. Further research will concentrate on extending the data visualization techniques so as to allow for the discovery of useful structures in visual data sets. We envisage this

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