Automated methods for image detection of cultural heritage: Overviews and perspectives.

Remote sensing data covering large geographical areas can be easily accessed and are being acquired with greater frequency. The massive volume of data requires an automated image analysis system. By taking advantage of the increasing availability of data using computer vision, we can design specific...

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Publicado en:Archaeological Prospection Vol. 30; no. 2; pp. 153 - 170
Autores principales: Câmara, Ariele, de Almeida, Ana, Caçador, David, Oliveira, João
Formato: Artículo
Publicado: Wiley-Blackwell Apr2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2023
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        10.1002/arp.1883
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        atl: Automated methods for image detection of cultural heritage: Overviews and perspectives.
      aug:
        au:
          Câmara, Ariele
          de Almeida, Ana
          Caçador, David
          Oliveira, João
        affil:
          Instituto Universitário de Lisboa (ISCTE‐IUL), Lisboa, Portugal
          Instituto Universitário de Lisboa (ISCTE‐IUL), Centro de Investigação em Ciências da Informação, Tecnologias e Arquitetura, Lisboa, Portugal
          Centre for Informatics and Systems of the University of Coimbra (CISUC), Coimbra, Portugal
          Instituto de Telecomunicações, Lisboa, Portugal
      su:
        Cultural property
        Remote sensing
        Image analysis
        Object recognition (Computer vision)
        Imaging systems
        Archaeological surveying
        Archaeology
      sug:
        subj:
          Cultural property
          Remote sensing
          Image analysis
          Object recognition (Computer vision)
          Imaging systems
          Archaeological surveying
          Archaeology
      keyword:
        archaeological monuments
        automated detection
        computer vision
        image analysis
        remote sensing
      ab: Remote sensing data covering large geographical areas can be easily accessed and are being acquired with greater frequency. The massive volume of data requires an automated image analysis system. By taking advantage of the increasing availability of data using computer vision, we can design specific systems to automate data analysis and detection of archaeological objects. In the past decade, there has been a rise in the use of automated methods to assist in the identification of archaeological sites in remote sensing imagery. These applications offer an important contribution to non‐intrusive archaeological exploration, helping to reduce the traditional human workload and time by signalling areas with a higher probability of presenting archaeological sites for exploration. This survey describes the state of the art of existing automated image analysis methods in archaeology and highlights the improvements thus achieved in the detection of archaeological monuments and areas of interest in landscape‐scale satellite and aerial imagery. It also presents a discussion of the benefits and limitations of automatic detection of archaeological structures, proposing new approaches and possibilities.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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