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oapen-20.500.12657-553852022-06-01T03:29:44Z Image Understanding by Socializing the Semantic Gap URICCHIO, TIBERIO bic Book Industry Communication::A The arts::AM Architecture::AMA Theory of architecture bic Book Industry Communication::A The arts::AM Architecture::AMC Architectural structure & design bic Book Industry Communication::K Economics, finance, business & management::KN Industry & industrial studies bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBC Engineering: general bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBD Technical design bic Book Industry Communication::T Technology, engineering, agriculture::TB Technology: general issues::TBG Engineering graphics & technical drawing 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. 2022-05-31T10:28:16Z 2022-05-31T10:28:16Z 2017 book ONIX_20220531_9788864535777_669 2612-8020 9788864535777 9788864535760 9788892731646 https://library.oapen.org/handle/20.500.12657/55385 eng Premio Tesi di Dottorato application/pdf Attribution 4.0 International 9788864535777.pdf https://books.fupress.com/isbn/9788864535777 Firenze University Press 10.36253/978-88-6453-577-7 10.36253/978-88-6453-577-7 bf65d21a-78e5-4ba2-983a-dbfa90962870 9788864535777 9788864535760 9788892731646 66 150 Florence open access
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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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