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GAT: a Graphical Annotation Tool for semantic regions

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Abstract

This article presents GAT, a Graphical Annotation Tool based on a region-based hierarchical representation of images. The proposed solution uses Partition Trees to navigate through the image segments which are automatically defined at different spatial scales. Moreover, the system focuses on the navigation through ontologies for a semantic annotation of objects and of the parts that compose them. The tool has been designed under usability criteria to minimize the user interaction by trying to predict the future selection of regions and semantic classes. The implementation uses MPEG-7/XML input and output data to allow interoperability with any type of Partition Tree. This tool is publicly available and its source code can be downloaded under a free software license.

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Notes

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    http://gps-tsc.upc.es/imatge/i3media/gat/

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Acknowledgements

This work was partially founded by the Catalan Broadcasting Corporation (CCMA) and Mediapro S.L. through the Spanish project CENIT-2007-1012 i3media, by TEC2007-66858/TCM PROVEC project of the Spanish Government and by a grant from the Commissioner for Universities and Research of the Innovation, Universities and Industry Department of the Catalan Government.

Copyright warnings

The “TV anchor” and “Formula 1” key-frames used in this paper belongs to TVC, Televisió de Catalunya, and is copyright protected. This key-frame has been provided by TVC with the only goal of research under the framework of the i3media project.

The “soccer” key-frame used in this paper belongs to MEDIAPRO, S.L., and is copyright protected. This key-frame has been provided by MEDIAPRO, S.L. with the only goal of research under the framework of the i3media project.

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Correspondence to Xavier Giro-i-Nieto.

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Giro-i-Nieto, X., Camps, N. & Marques, F. GAT: a Graphical Annotation Tool for semantic regions. Multimed Tools Appl 46, 155–174 (2010). https://doi.org/10.1007/s11042-009-0389-2

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Keywords

  • Annotation
  • Region
  • Ontology
  • Navigation
  • Semantic
  • Hierarchical