By Shi-Kuo Chang (auth.), Robert Laurini (eds.)
Presently, in our international, visible details dominates. The flip of the millenium marks the age of visible details structures. Enabled by means of photo sensors of every kind turning electronic, visible details won't in basic terms improve the price of latest details, it's going to additionally open up a brand new horizon of formerly untapped info resources. there's a large call for for visible info entry from the shopper. in addition, the dealing with of visible details is boosted via the fast elevate of and net functions. complicated expertise for visible details platforms is extra urgently wanted than ever ahead of: not just new computational ways to retrieve, index, compress and discover pictorial details, but in addition new metaphors to prepare consumer interfaces. additionally, new rules and algorithms are wanted which permit entry to huge databases of electronic photographs and movies. eventually we must always now not put out of your mind new structures with visible interfaces integrating the above elements into new sorts of photograph, video or multimedia databases and hyperdocuments. All of those applied sciences will permit the development of platforms which are greatly diverse from traditional info structures. Many novel concerns might want to be addressed: question formula for pictorial details, consistency administration thereof, indexing and assessing the standard of those platforms. traditionally, the expression visible details structures could be understood both as a procedure for picture details or as visible approach for any type information.
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Additional info for Advances in Visual Information Systems: 4th International Conference, VISUAL 2000 Lyon, France, November 2–4, 2000 Proceedings
These techniques need rethinking when used for image retrieval. Most prominent problem is tile semantic gap between the pictorial properties a system call derive automatically from the image on the one hand and tile lingual interpretation of tile image the user has in mind. Due to the semantic gap~ tile meaning of an image can only be defined in context. As a consequence, image retrieval requires active participation of the user to a much higher degree than categorized querying 20. In content-based image retrieval, interaction is a complex interplay between tile user, tile images, their features, and their semantic interpretation, hi this paper we explore tile relations and provide a framework which unifies existing methods.
Both positive and negative examples are used to compute tile final weight. The weights for tile different features ill the feature class, are taken as tile inverse of tile variance of the feature over positive examples. The feedback Ai in 20 leads to new user desired dista*lces between some of the pairs of images in IQ. ity function should be updated to match ill optima way the new distances. Tile optimization problem is ill-posed usually. A regularization term is introduced which limits the departure from the natural distaalce fmlction.
Ghetlreab, M. D. C. Jaffe. SCHEMed : a visual database tool for definition and entry of medical image data. In R. Jaln and S. Santini, editors, P~vceedings of Visual ~nformation Systems, pages 189 196. Knowledge Systems Institut% 1997. 8. A. G n p t a and R. Jain. Visual information retrieval. Communications of the ACM~ 40(5):71 79, 1997. 9. A. Hiroike, Y. Musha, A. Snglmoto, axld Y. Mori. Visualization of infi)rmation spaces to retrieve an( browse image data. P. M. Smeulders, editors~ Proceedings of Visual 99: nte~vsational Co~ference on Visual Infof mation System,s: volume 1614 of Lecture Notes in Compute~v Science, pages 155 162, 1999.