SoMIAP: Social media images analysis and prediction framework

TL;DR

This paper introduces SoMIAP, a framework that analyzes social media images using place and face recognition to predict user locations, aiding security efforts by providing insights from personal photos.

Contribution

It presents a novel combined approach for location prediction from social media images using place and face recognition techniques.

Findings

Effective location prediction demonstrated through experimental results

Combines place and face recognition for improved accuracy

Potential applications in security monitoring and criminal tracking

Abstract

The personal photos captured and submitted by users on social networks can provide several interesting insights about the location of the user, 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.