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Seminar Details

Date 15-12-2005
Time 15:30
Room/Location Sala conferenze 322, 3 piano
Title Approximate Nearest-Neighbor Searches: Application to Content-Based Image Retrieval
Speaker Sid-Ahmed Berrani, Ph.D.
Affiliation France Telecom R&D - TECH/IRIS , 4, rue du Clos Courtel - BP 91226. 35512 Cesson Sévigné Cedex. Fran
Link http://www.irisa.fr/texmex/Sid-Ahmed.Berrani/
Abstract Content-based image retrieval systems rely on image processing methods to automatically describe the images and on multidimensional indexing techniques to reduce the cost of similarity searches. Unfortunately, the existing multidimensional indexing techniques are not well-adapted to the properties of the image descriptors (dimension, distribution...). Their performance degrades drastically when the dimension of image descriptors increases (dimensionality curse problem). In this talk, this problem will be analyzed and a new efficient method of nearest-neighbor (NN) searches will be presented. The idea of this method is to reduce the retrieval cost by searching for the approximate neighbors of the query instead of searching for the exact result, realizing hence a trade-off between result quality and query execution time. This method allows, however, a fine and intuitive probabilistic control of the precision of the search. In the second part of the talk, an application of the proposed NN search method within a real CBIR system for image copy identification will then be presented. Keywords: Multimedia Indexing, Content-Based Image Retrieval, Similarity Searches, (Approximate) Nearest-Neighbor Searches, Dimensionality Curse
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