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Computer Vision for Multimedia Geolocation in Human Trafficking Investigation: A Systematic Literature Review
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The task of multimedia geolocation is becoming an increasingly essential component of the digital forensics toolkit to effectively combat human trafficking, child sexual exploitation, and other illegal acts. Typically, metadata-based geolocation information is stripped when multimedia content is shared via instant messaging and social media. The intricacy of geolocating, geotagging, or finding geographical clues in this content is often overly burdensome for investigators. Recent research has shown that contemporary advancements in artificial intelligence, specifically computer vision and deep learning, show significant promise towards expediting the multimedia geolocation task. This systematic literature review thoroughly examines the state-of-the-art leveraging computer vision techniques for multimedia geolocation and assesses their potential to expedite human trafficking investigation. This includes a comprehensive overview of the application of computer vision-based approaches to multimedia geolocation, identifies their applicability in combating human trafficking, and highlights the potential implications of enhanced multimedia geolocation for prosecuting human trafficking. 123 articles inform this systematic literature review. The findings suggest numerous potential paths for future impactful research on the subject.
Forward citations
Cited by 2 Pith papers
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Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation
A generative model using diffusion and Riemannian flow matching on the sphere achieves state-of-the-art visual geolocation and outputs full probability maps over possible locations.
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Ask before you Build: Rethinking AI-for-Good in Human Trafficking Interventions
Radical Questioning, a five-step pre-design ethics framework, redirects an AI human trafficking project from ad surveillance to survivor-centered evidence support.
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