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.
University of Florence, Italy - ORCID: 0000-0003-1025-4541
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
Metadata License
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
2612-8039
Series E-ISSN
2612-8020