SoMIAP: Social Media Images Analysis and Prediction Framework

Yonghao Shi, Gueltoum Bendiab, Stavros Shiaeles, Nick Savage

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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The personal photos captured and submitted by users on social networks can provide several interesting insights about the user’s location; which is a key indicator of their daily activities. This information is invaluable for security organisations, especially for security monitoring and tracking criminal activities. Hence, we propose in this paper a novel approach for location prediction based on the image analysis of the photos posted on social media. Our approach combines two main methods to perform the image analysis; place and face recognition. The first method is used to determine the location area in the analysed image. The second is used to identify people in the analysed image, by locating a face in the image and comparing it with a dataset of images that have been collected from different social platforms. The effectiveness of the proposed approach is demonstrated through performance analysis and experimental results.
Original languageEnglish
Title of host publicationInternet of Things, Smart Spaces, and Next Generation Networks and Systems
Subtitle of host publication20th International Conference, NEW2AN 2020, and 13th Conference, ruSMART 2020, St. Petersburg, Russia, August 26–28, 2020, Proceedings, Part I
EditorsOlga Galinina, Sergey Andreev, Sergey Balandin, Yevgeni Koucheryavy
ISBN (Electronic)9783030657260
ISBN (Print)9783030657253
Publication statusPublished - 22 Dec 2020

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


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