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Bayesian Decision Versus Voting for Image Retrieval

Roger Mohr 1 Sylvaine Picard 1 Cordelia Schmid 1 
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : Image retrieval from image databases is usually performed by using global image characteristics. However the use of local image information is highly desirable when only part of the image is of interest. An original solution was introduced in [9] using invariant local signal characteristics. This paper extends this contribution by extending the set of invariants considered to allow illumination change. Then it is shown that the invariant distribution is far from uniform and a probabilistic indexing scheme is proposed. Experimental results validate the approch and the different methods are discussed.
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Submitted on : Wednesday, December 22, 2010 - 3:27:38 PM
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Roger Mohr, Sylvaine Picard, Cordelia Schmid. Bayesian Decision Versus Voting for Image Retrieval. 7th International Conference on Computer Analysis of Images and Patterns (CAIP '97), Sep 1997, Kiel, Germany. pp.376--383, ⟨10.1007/3-540-63460-6_140⟩. ⟨inria-00548350⟩



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