An interactive Platform for Representing, Interlinking and Analyzing Content on Art
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/151777 |
Resumo: | Unfortunately, many art objects such as paintings and sculptures are not yet cataloged in digital form. Often not even in printed catalogs or books. This circumstance provides a considerable obstacle for obtaining information from different collections within mu- seums or private collections all over the world. Because a significant number of works of art are also never cataloged, either because the owners lack the knowledge to do so or because there isn’t a simple tool to help the cataloging process, by providing a large amount of information in an accurate way, a significant number of these works of art also remain unknown to the world. With the help of machine learning algorithms and tools that can interpret images contents, a platform is to be created that offers a simple data acquisition from art pieces. In addition to simpler technical attributes such as style and type of art, more detailed information such as probable artist, materials, and decade of creation could already be suggested to the user during the data acquisition. This is possible thanks to the algorithms that can analyze images of the object in question. Alongside these suggestions, there would be the possibility to interlink data by multiple features in order to get similar art pieces to the submitted one. From the user utilization of the platform, the growing data set shall be linked with each other, visualized in an interactive platform, and finally serve to improve the analysis of new art objects. The creation of this platform made it feasible to offer a wide amount of information about any work of art. Four separate image classification models that could categorize art pieces based on their author, style, decade, and type were developed. To improve the prediction power of these, a number of strategies were studied and applied. Further details, including a set of relevant tags, the most dominant colors, and the materials utilized in the pieces of art, were also provided using Google Cloud Vision API. The platform’s whole infrastructure was built with these features and best practices in mind. |
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An interactive Platform for Representing, Interlinking and Analyzing Content on ArtArtPlatformMachine LearningAlgorithmCatalogInterlinkingDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaUnfortunately, many art objects such as paintings and sculptures are not yet cataloged in digital form. Often not even in printed catalogs or books. This circumstance provides a considerable obstacle for obtaining information from different collections within mu- seums or private collections all over the world. Because a significant number of works of art are also never cataloged, either because the owners lack the knowledge to do so or because there isn’t a simple tool to help the cataloging process, by providing a large amount of information in an accurate way, a significant number of these works of art also remain unknown to the world. With the help of machine learning algorithms and tools that can interpret images contents, a platform is to be created that offers a simple data acquisition from art pieces. In addition to simpler technical attributes such as style and type of art, more detailed information such as probable artist, materials, and decade of creation could already be suggested to the user during the data acquisition. This is possible thanks to the algorithms that can analyze images of the object in question. Alongside these suggestions, there would be the possibility to interlink data by multiple features in order to get similar art pieces to the submitted one. From the user utilization of the platform, the growing data set shall be linked with each other, visualized in an interactive platform, and finally serve to improve the analysis of new art objects. The creation of this platform made it feasible to offer a wide amount of information about any work of art. Four separate image classification models that could categorize art pieces based on their author, style, decade, and type were developed. To improve the prediction power of these, a number of strategies were studied and applied. Further details, including a set of relevant tags, the most dominant colors, and the materials utilized in the pieces of art, were also provided using Google Cloud Vision API. The platform’s whole infrastructure was built with these features and best practices in mind.Infelizmente, muitas peças de arte, como pinturas e esculturas, ainda não estão cataloga- das em formato digital. Muitas vezes nem mesmo em catálogos ou livros. Esta circuns- tância constitui um obstáculo considerável para a aquisição de informação de diferentes coleções de museus ou coleções particulares em todo o mundo. Igualmente, uma grande quantidade de peças de arte não são catalogadas tanto por falta de conhecimentos por parte do proprietário ou por falta de um método simples de as tornar públicas. Com a ajuda de algoritmos e ferramentas de aprendizagem computacional que conse- guem interpretar o conteúdo de imagens, uma plataforma que oferece uma ferramenta de aquisição de dados de peças de arte será criada. Além de atributos técnicos mais simples como o estilo e tipo de arte, informações mais detalhadas como o artista provável, mate- riais e a década de criação poderiam ser sugeridas ao utilizador durante a aquisição dos dados. Isto é possível graças aos algoritmos que conseguem analisar imagens do objeto em questão. Além destas sugestões, haveria a possibilidade de interligar os dados por diferentes atributos de forma a obter peças de arte semelhantes à que fora submetida. A partir da utilização da plataforma pelo usuário, o crescente conjunto de dados deve ser interligado entre si, visualizado numa plataforma interativa, e por fim ser utilizado de forma a melhorar a análise de novos objetos de arte. Com o desenvolvimento da plataforma, é possível oferecer uma grande variedade de informação. Foram desenvolvidos quatro diferentes algoritmos que conseguem catego- rizar uma peça de arte de acordo com o seu artista, estilo, década e tipo. Para melhorar a performance destes algorimos, um conjunto de técnicas foram estudadas e aplicadas. Mais informação, como um conjunto de palavras relevantes, as cores mais dominates, e os materiais usados nas peças de arte, poderam também ser sugeridas usando a Google Cloud Vision API. Toda a infraestrutura da plataforma foi desenvolvida tendo em conta as funcionalidades necessárias e as melhores práticas.Heimann, ErikMedeiros, PedroRUNRibeiro, Guilherme Figueiredo2023-04-13T09:24:36Z2022-112022-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/151777enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:34:09Zoai:run.unl.pt:10362/151777Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:41.534057Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art |
title |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art |
spellingShingle |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art Ribeiro, Guilherme Figueiredo Art Platform Machine Learning Algorithm Catalog Interlinking Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
title_short |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art |
title_full |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art |
title_fullStr |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art |
title_full_unstemmed |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art |
title_sort |
An interactive Platform for Representing, Interlinking and Analyzing Content on Art |
author |
Ribeiro, Guilherme Figueiredo |
author_facet |
Ribeiro, Guilherme Figueiredo |
author_role |
author |
dc.contributor.none.fl_str_mv |
Heimann, Erik Medeiros, Pedro RUN |
dc.contributor.author.fl_str_mv |
Ribeiro, Guilherme Figueiredo |
dc.subject.por.fl_str_mv |
Art Platform Machine Learning Algorithm Catalog Interlinking Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
topic |
Art Platform Machine Learning Algorithm Catalog Interlinking Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
description |
Unfortunately, many art objects such as paintings and sculptures are not yet cataloged in digital form. Often not even in printed catalogs or books. This circumstance provides a considerable obstacle for obtaining information from different collections within mu- seums or private collections all over the world. Because a significant number of works of art are also never cataloged, either because the owners lack the knowledge to do so or because there isn’t a simple tool to help the cataloging process, by providing a large amount of information in an accurate way, a significant number of these works of art also remain unknown to the world. With the help of machine learning algorithms and tools that can interpret images contents, a platform is to be created that offers a simple data acquisition from art pieces. In addition to simpler technical attributes such as style and type of art, more detailed information such as probable artist, materials, and decade of creation could already be suggested to the user during the data acquisition. This is possible thanks to the algorithms that can analyze images of the object in question. Alongside these suggestions, there would be the possibility to interlink data by multiple features in order to get similar art pieces to the submitted one. From the user utilization of the platform, the growing data set shall be linked with each other, visualized in an interactive platform, and finally serve to improve the analysis of new art objects. The creation of this platform made it feasible to offer a wide amount of information about any work of art. Four separate image classification models that could categorize art pieces based on their author, style, decade, and type were developed. To improve the prediction power of these, a number of strategies were studied and applied. Further details, including a set of relevant tags, the most dominant colors, and the materials utilized in the pieces of art, were also provided using Google Cloud Vision API. The platform’s whole infrastructure was built with these features and best practices in mind. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11 2022-11-01T00:00:00Z 2023-04-13T09:24:36Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/151777 |
url |
http://hdl.handle.net/10362/151777 |
dc.language.iso.fl_str_mv |
eng |
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eng |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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