Towards Robust Evaluation of Aesthetic and Photographic Quality Metrics: Insights from a Comprehensive Dataset

UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.grupoInvRedes de Neuronas Artificiais e Sistemas Adaptativos -Informática Médica e Diagnóstico Radiolóxico (RNASA - IMEDIR)es_ES
UDC.issue8223586es_ES
UDC.journalTitleComplexityes_ES
UDC.volume2024es_ES
dc.contributor.authorSantos, Iria
dc.contributor.authorCasal, Miguel A.
dc.contributor.authorCorreia, Joao
dc.contributor.authorTorrente-Patiño, Álvaro
dc.contributor.authorMachado, Penousal
dc.contributor.authorRomero, Juan
dc.date.accessioned2024-10-28T10:59:55Z
dc.date.available2024-10-28T10:59:55Z
dc.date.issued2024
dc.description.abstract[Abstract]: In recent years, the development of metrics to evaluate image aesthetics and photographic quality has proliferated. However, validating these metrics presents challenges due to the inherently subjective nature of aesthetics and photographic quality, which can be influenced by cultural contexts and individual preferences that evolve over time. This article presents a novel validation methodology utilizing a dataset assessed by individuals from two distinct nationalities: the United States and Spain. Evaluation criteria include photographic quality and aesthetic value, with the dataset comprising images previously rated on the DPChallenge photographic portal. We analyze the correlation between these values and provide the dataset for future research endeavors. Our investigation encompasses several metrics, including BRISQUE for assessing photographic quality, NIMA aesthetic and NIMA technical for evaluating both aesthetic and technical aspects, Diffusion Aesthetics (employed in Stable Diffusion), and PhotoILike for gauging the commercial appeal of real estate images. Our findings reveal a significant correlation between the Diffusion Aesthetics metric and aesthetic measures, as well as with the NIMA aesthetics metric, suggesting them as good potential candidates to capture aesthetic value.es_ES
dc.description.sponsorshipCITIC, as a Research Center of the Galician University System, was funded by the Department of Culture, Education and University of the Xunta de Galicia through the European Regional Development Fund (ERDF) with an 80% Operational Program ERDF Galicia 2014-2020. This work was supported by the General Directorate of Culture, Education and University Management of Xunta de Galicia (Ref. GRC2014/049) and the European Fund for Regional Development (FEDER) allocated by the European Union, the Portuguese Foundation for Science and Technology for the development of project SBIRC (Ref. PTDC/EIA-EIA/ 115667/2009); I.P./MCTES through national funds (PIDDAC), within the scope of CISUC R&D Unit-UIDB/00326/2020 or project code UIDP/00326/2020 and under the grant SFRH/BD/143553/2019; Xunta de Galicia (Ref. XUGAPGIDIT- 10TIC105008-PR); and the Spanish Ministry for Science and Technology (Ref. TIN2008-06562/TIN). Also, this work received funding with reference PID2020-118362RB-I00 from the State Program of R +D+ i oriented to the Challenges of the Society of the Spanish Ministry of Science, Innovation, and Universities. We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.es_ES
dc.description.sponsorshipXunta de Galicia; GRC2014/049es_ES
dc.description.sponsorshipXunta de Galicia; XUGA-PGIDIT-10TIC105008-PRes_ES
dc.description.sponsorshipPortugal. Fundação para a Ciência e a Tecnologia; PTDC/EIA-EIA/115667/2009es_ES
dc.description.sponsorshipPortugal. Fundação para a Ciência e a Tecnologia; SFRH/BD/143553/2019es_ES
dc.description.sponsorshipCentro de Informática e Sistemas da Universidade de Coimbra; UIDP/00326/2020es_ES
dc.identifier.citationI. Santos, M. A. Casal, J. Correia, Á. Torrente-Patiño, P. Machado, and J. Romero, "Towards Robust Evaluation of Aesthetic and Photographic Quality Metrics: Insights from a Comprehensive Dataset", Complexity, Vol. 2024, 8223586, 2024, https://doi.org/10.1155/2024/8223586es_ES
dc.identifier.doi10.1155/2024/8223586
dc.identifier.urihttp://hdl.handle.net/2183/39834
dc.language.isoenges_ES
dc.publisherJohn Wiley and Sons Inces_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN/Plan Nacional de I+D+i 2008-2011/TIN2008-06562/ES/APLICACION DE METRICAS PARA LA CLASIFICACION DE IMAGENES SEGUN CRITERIOS ESTILISTICOS Y ESTETICOSes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-118362RB-I00/ES/PREDICCION DE LA PERCEPCION ESTETICA HUMANA MEDIANTE INTELIGENCIA ARTIFICIAL/es_ES
dc.relation.urihttps://doi.org/10.1155/2024/8223586es_ES
dc.rightsAttribution 4.0 International (CC BY)es_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectAesthetic metricses_ES
dc.subjectAesthetic qualitieses_ES
dc.subjectAesthetic valuees_ES
dc.subjectCultural contextes_ES
dc.subjectEvaluation criteriaes_ES
dc.subjectImage Aestheticses_ES
dc.subjectIndividual preferencees_ES
dc.subjectPhotographic-qualityes_ES
dc.subjectQuality metriceses_ES
dc.subjectValidation methodologieses_ES
dc.titleTowards Robust Evaluation of Aesthetic and Photographic Quality Metrics: Insights from a Comprehensive Datasetes_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication4b05c41f-26dc-44a6-8928-adf2847aae27
relation.isAuthorOfPublication3a05ff0e-ae38-4afc-9fdc-0e79807bd556
relation.isAuthorOfPublicationf9985d38-4af2-414c-8e8c-0e46c78c60e7
relation.isAuthorOfPublication.latestForDiscovery4b05c41f-26dc-44a6-8928-adf2847aae27

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