Perceptual Metrics for Image Database Navigation

distributions of the image features should be represented by a collection of data that is small, for efficiency, but rich enough to reproduce the essential information. The issue of relevance to human perception has been resolved by the ...

Perceptual Metrics for Image Database Navigation

The increasing amount of information available in today's world raises the need to retrieve relevant data efficiently. Unlike text-based retrieval, where keywords are successfully used to index into documents, content-based image retrieval poses up front the fundamental questions how to extract useful image features and how to use them for intuitive retrieval. We present a novel approach to the problem of navigating through a collection of images for the purpose of image retrieval, which leads to a new paradigm for image database search. We summarize the appearance of images by distributions of color or texture features, and we define a metric between any two such distributions. This metric, which we call the "Earth Mover's Distance" (EMD), represents the least amount of work that is needed to rearrange the mass is one distribution in order to obtain the other. We show that the EMD matches perceptual dissimilarity better than other dissimilarity measures, and argue that it has many desirable properties for image retrieval. Using this metric, we employ Multi-Dimensional Scaling techniques to embed a group of images as points in a two- or three-dimensional Euclidean space so that their distances reflect image dissimilarities as well as possible. Such geometric embeddings exhibit the structure in the image set at hand, allowing the user to understand better the result of a database query and to refine the query in a perceptually intuitive way.

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Perceptual Metrics for Image Database Navigation
Language: en
Pages: 137
Authors: Yossi Rubner, Carlo Tomasi
Categories: Technology & Engineering
Type: BOOK - Published: 2013-03-14 - Publisher: Springer Science & Business Media

The increasing amount of information available in today's world raises the need to retrieve relevant data efficiently. Unlike text-based retrieval, where keywords are successfully used to index into documents, content-based image retrieval poses up front the fundamental questions how to extract useful image features and how to use them for
Perceptual Metrics for Image Database Navigation
Language: en
Pages: 137
Authors: Yossi Rubner, Carlo Tomasi
Categories: Technology & Engineering
Type: BOOK - Published: 2012-12-05 - Publisher: Springer

The increasing amount of information available in today's world raises the need to retrieve relevant data efficiently. Unlike text-based retrieval, where keywords are successfully used to index into documents, content-based image retrieval poses up front the fundamental questions how to extract useful image features and how to use them for
Perceptual Metrics for Image Database Navigation
Language: en
Pages: 161
Authors: Yossi Rubner
Categories: Database management
Type: BOOK - Published: 1999 - Publisher:

Books about Perceptual Metrics for Image Database Navigation
Content Engineering
Language: de
Pages: 179
Authors: Michael A. Herzog
Categories: Digital communications
Type: BOOK - Published: 2007 - Publisher: GITO mbH Verlag

Books about Content Engineering
Image and Video Retrieval
Language: en
Pages: 392
Authors: Michael S. Lew, Nicu Sebe, John P. Eakins
Categories: Computers
Type: BOOK - Published: 2002-07-03 - Publisher: Springer Science & Business Media

Finally,wearegrateful tooursponsors,theBritishComputerSocietyInformationRetrievalSpecialist Group,theBritishMachineVisionAssociation(BMVA),theInstituteforImage DataResearch,UniversityofNorthumbria,theInstitutionofElectricalEn- neers(IEE),andtheLeidenInstituteofAdvancedComputerScience(LIACS), LeidenUniversiy. May2002 MichaelS. Lew NicuSebe JohnP. Eakins International Conference an Image andVideo Retrieval 2002 Organization Organizing Committee OrganizingCommitteeChair: JohnP. Eakins (UniversityofNorthumbria,UK) TechnicalProgramChair: MichaelS.