Monograph

Image Understanding by Socializing the Semantic Gap

  • Tiberio Uricchio,

Several technological developments like the Internet, mobile devices and Social Networks have spurred the sharing of images in unprecedented volumes, making tagging and commenting a common habit. Despite the recent progress in image analysis, the problem of Semantic Gap still hinders machines in fully understand the rich semantic of a shared photo. In this book, we tackle this problem by exploiting social network contributions. A comprehensive treatise of three linked problems on image annotation is presented, with a novel experimental protocol used to test eleven state-of-the-art methods. Three novel approaches to annotate, under stand the sentiment and predict the popularity of an image are presented. We conclude with the many challenges and opportunities ahead for the multimedia community.

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Tiberio Uricchio

University of Florence, Italy - ORCID: 0000-0003-1025-4541

Tiberio Uricchio is a postdoctoral researcher at the University of Florence, Italy. He earned his Ph.D. in computer engineering from the University of Florence in 2016 with an awarded thesis on image understanding. He gave tutorials at three international conferences (ACM-MM’15, CVPR’16, ICIAP’17).
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PDF
  • Publication Year: 2017
  • Pages: 150
  • eISBN: 978-88-6453-577-7
  • Content License: CC BY 4.0
  • © 2017 Author(s)

XML
  • Publication Year: 2017
  • eISBN: 978-88-9273-164-6
  • Content License: CC BY 4.0
  • © 2017 Author(s)

PRINT
  • Publication Year: 2017
  • Pages: 150
  • eISBN: 978-88-6453-576-0
  • Content License: CC BY 4.0
  • © 2017 Author(s)

Bibliographic Information

Book Title

Image Understanding by Socializing the Semantic Gap

Authors

Tiberio Uricchio

Peer Reviewed

Number of Pages

150

Publication Year

2017

Copyright Information

© 2017 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/978-88-6453-577-7

ISBN Print

978-88-6453-576-0

eISBN (pdf)

978-88-6453-577-7

eISBN (xml)

978-88-9273-164-6

Series Title

Premio Tesi di Dottorato

Series Issn ISSN

2612-8039

Series E-Issn

2612-8020

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