This paper describes a complete architecture for the interactive exploration and annotation of artistic collections. In particular the focus is on Renaissance illuminated manuscripts, which typically contain thousands of pictures, used to comment or embellish the manuscript Gothic text. The final aim is to create a human centered multimedia application allowing the non practitioners to enjoy these masterpieces and expert users to share their knowledge. The system is composed by a modern user interface for browsing, surfing and querying, an automatic segmentation module, to ease the initial picture extraction task, and a similarity based retrieval engine, used to provide visually assisted tagging capabilities. A relevance feedback procedure is included to further refine the results. Experiments are reported regarding the adopted visual features based on covariance matrices and the Mean Shift Feature Space Warping relevance feedback. Finally some hints on the user interface for museum installations are discussed.
Surfing on Artistic Documents with Visually Assisted Tagging / Grana, Costantino; Borghesani, Daniele; Cucchiara, Rita. - STAMPA. - (2010), pp. 1343-1352. (Intervento presentato al convegno 18th International Conference on Multimedia (ACM Multimedia 2010) tenutosi a Florence, Italy nel Oct 25-29) [10.1145/1873951.1874216].
Surfing on Artistic Documents with Visually Assisted Tagging
GRANA, Costantino;BORGHESANI, Daniele;CUCCHIARA, Rita
2010
Abstract
This paper describes a complete architecture for the interactive exploration and annotation of artistic collections. In particular the focus is on Renaissance illuminated manuscripts, which typically contain thousands of pictures, used to comment or embellish the manuscript Gothic text. The final aim is to create a human centered multimedia application allowing the non practitioners to enjoy these masterpieces and expert users to share their knowledge. The system is composed by a modern user interface for browsing, surfing and querying, an automatic segmentation module, to ease the initial picture extraction task, and a similarity based retrieval engine, used to provide visually assisted tagging capabilities. A relevance feedback procedure is included to further refine the results. Experiments are reported regarding the adopted visual features based on covariance matrices and the Mean Shift Feature Space Warping relevance feedback. Finally some hints on the user interface for museum installations are discussed.Pubblicazioni consigliate
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