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HELPI VIZ: A Semantic image Annotation and Visualization Platform for Visually Impaired

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • Siddharth Prasad

    (National Institute of Technology, Department of Computer Applications)

  • Akhilesh Kumar Lodhi

    (National Institute of Technology, Department of Computer Applications)

  • Sarika Jain

    (National Institute of Technology, Department of Computer Applications)

Abstract

Getting appropriate data is the greatest need of today’s world, particularly for visually impaired, and when the data is in form of online media, its representation in different format is a major issue. We can solve this issue by commenting on (naming) the pictures using different content, to make the image simpler and more semantic for visually impaired individuals. Semantic annotation of pictures provides a way for semantic search of image with less difficulty, and gives ease in representation. This paper presents a user-friendly tool, called HELPI VIZ, for annotating, visualizing and navigating images using ontologies. It is designed to be used by everyone, including ontology experts and users not familiar with ontologies. It provides an accessible and understandable user interface that follows the “design-for-all” philosophy. It is a responsive web application for the visualization of annotated pictures and ontologies using sound and text. It provides a platform to increases tourism by making historical pictures of monuments and sculpture self-talking by annotating with text and sound. It can be used as a image visualization and search tool for online media content, it can used as educational tool kit for students and numerous all the more such applications.

Suggested Citation

  • Siddharth Prasad & Akhilesh Kumar Lodhi & Sarika Jain, 2020. "HELPI VIZ: A Semantic image Annotation and Visualization Platform for Visually Impaired," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 881-888, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_89
    DOI: 10.1007/978-3-030-41862-5_89
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