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dc.contributor.authorGomez Duran, Paula
dc.contributor.authorMohedano, Eva
dc.contributor.authorMcGuinness, Kevin
dc.contributor.authorGiró Nieto, Xavier
dc.contributor.authorO'Connor, Noel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2018-11-02T10:13:46Z
dc.date.available2018-11-02T10:13:46Z
dc.date.issued2018
dc.identifier.citationGomez, P., Mohedano, E., McGuinness, K., Giro, X., O'Connor, N. Demonstration of an open source framework for qualitative evaluation of CBIR systems. A: ACM Multimedia Conference. "Proceedings of 2018 ACM Multimedia Conference, Seoul, Republic of Korea, October 22-26, 2018 (MM’18)". New York: Association for Computing Machinery (ACM), 2018, p. 1256-1257.
dc.identifier.isbn978-1-4503-5665-7
dc.identifier.otherhttps://imatge.upc.edu/web/publications/demonstration-open-source-framework-qualitative-evaluation-cbir-systems
dc.identifier.urihttp://hdl.handle.net/2117/123448
dc.description.abstractEvaluating image retrieval systems in a quantitative way, for example by computing measures like mean average precision, allows for objective comparisons with a ground-truth. However, in cases where ground-truth is not available, the only alternative is to collect feedback from a user. Thus, qualitative assessments become important to better understand how the system works. Visualizing the results could be, in some scenarios, the only way to evaluate the results obtained and also the only opportunity to identify that a system is failing. This necessitates developing a User Interface (UI) for a Content Based Image Retrieval (CBIR) system that allows visualization of results and improvement via capturing user relevance feedback. A well-designed UI facilitates understanding of the performance of the system, both in cases where it works well and perhaps more importantly those which highlight the need for improvement. Our open-source system implements three components to facilitate researchers to quickly develop these capabilities for their retrieval engine. We present: a web-based user interface to visualize retrieval results and collect user annotations; a server that simplifies connection with any underlying CBIR system; and a server that manages the search engine data.
dc.format.extent2 p.
dc.language.isoeng
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Sistemes experts
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subject.lcshImage processing--Digital techniques
dc.subject.lcshDigital video
dc.subject.lcshArtificial intelligence
dc.subject.otherretrieval
dc.subject.otherdeep learning
dc.subject.otheropen source
dc.subject.otheruser interface
dc.subject.othervisual search
dc.subject.othercontent-based image retrieval
dc.titleDemonstration of an open source framework for qualitative evaluation of CBIR systems
dc.typeConference lecture
dc.subject.lemacImatges -- Processament -- Tècniques digitals
dc.subject.lemacVídeo digital
dc.subject.lemacIntel·ligència artificial
dc.contributor.groupUniversitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
dc.identifier.doi10.1145/3240508.3241395
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://dl.acm.org/citation.cfm?id=3241395
dc.rights.accessOpen Access
drac.iddocument23443309
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/2PE/ TEC2016-75976-R
upcommons.citation.authorGomez, P., Mohedano, E., McGuinness, K., Giro, X., O'Connor, N.
upcommons.citation.contributorACM Multimedia Conference
upcommons.citation.pubplaceNew York
upcommons.citation.publishedtrue
upcommons.citation.publicationNameProceedings of 2018 ACM Multimedia Conference, Seoul, Republic of Korea, October 22-26, 2018 (MM’18)
upcommons.citation.startingPage1256
upcommons.citation.endingPage1257


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