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      Global Semantic Classification of Scenes using Power Spectrum Templates

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      Challenge of Image Retrieval (CIR)

      Image Retrieval

      25th - 26th February 1999

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          Abstract

          Scene recognition and content-based procedures are of great interest for image indexing applications processing very large databases. Knowing the context of a scene, a retrieval system may compute its semantic category in advance and filter out scenes belonging to irrelevant classes.

          In this paper, we introduce a computational approach which classifies and organises real-world scenes along broad semantic axes. Fundamental to our approach is the computation of global spectral templates providing a continuous organisation of scenes between two categories. These templates encode the structure which is discriminant between two categories. We propose a hierarchical procedure of two stages, that organises images along three semantic axis. Firstly, all the scenes are classified according to an Artificial to Natural axis. Then, natural scenes are organised along the Open to Closed axis whereas artificial environments are classified according to the Expanded to Enclosed scenes axis.

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          Author and article information

          Conference
          February 1999
          February 1999
          : 1-11
          Affiliations
          Laboratoire des Images et des Signaux (LIS)

          Institut National Polytechnique de Grenoble (INPG)

          Grenoble, France
          Article
          10.14236/ewic/CIR1999.9
          © Aude Oliva et al. Published by BCS Learning and Development Ltd. Challenge of Image Retrieval

          This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

          Challenge of Image Retrieval
          CIR
          Newcastle upon Tyne, UK
          25th - 26th February 1999
          Electronic Workshops in Computing (eWiC)
          Image Retrieval
          Product
          Product Information: 1477-9358BCS Learning & Development
          Self URI (journal page): https://ewic.bcs.org/
          Categories
          Electronic Workshops in Computing

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