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Erschienen in:
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2016 | OriginalPaper | Buchkapitel

PicHunt: Social Media Image Retrieval for Improved Law Enforcement

verfasst von : Sonal Goel, Niharika Sachdeva, Ponnurangam Kumaraguru, A. V. Subramanyam, Divam Gupta

Erschienen in: Social Informatics

Verlag: Springer International Publishing

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Abstract

First responders are increasingly using social media to identify and reduce crime for well-being and safety of the society. Images shared on social media hurting religious, political, communal and other sentiments of people, often instigate violence and create law & order situations in society. This results in the need for first responders to inspect the spread of such images and users propagating them on social media. In this paper, we present a comparison between different hand-crafted features and a Convolutional Neural Network (CNN) model to retrieve similar images, which outperforms state-of-art hand-crafted features. We propose an Open-Source-Intelligent (OSINT) real-time image search system, robust to retrieve modified images that allows first responders to analyze the current spread of images, sentiments floating and details of users propagating such content. The system also aids officials to save time of manually analyzing the content by reducing the search space on an average by 67 %.

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Vorheriges Kapitel Determining the Veracity of Rumours on Twitter
Nächstes Kapitel TwitterNews+: A Framework for Real Time Event Detection from the Twitter Data Stream
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Metadaten
Titel
PicHunt: Social Media Image Retrieval for Improved Law Enforcement
verfasst von
Sonal Goel
Niharika Sachdeva
Ponnurangam Kumaraguru
A. V. Subramanyam
Divam Gupta
Copyright-Jahr
2016
Buch
Social Informatics

Print ISBN: 978-3-319-47879-1

Electronic ISBN: 978-3-319-47880-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-47880-7_13

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