"Identification and tracing is the ability to trace, attribute, and confirm the identity of a person, location or activity to evidential levels, such as tracing missing persons.
Policing seek a step-change in our ability to process and fuse audio-visual materials, from CCTV, ANPR (Automatic Number Plate Recognition), video, smart doorbells, smartphones, and social media, as well as materials from developing platforms such as virtual reality, online gaming, and the metaverse. Challenges include collection, processing, and storage (of usually large files), identifying manipulation or spoofing, working with still compared to moving images, and maintaining the evidential chain. Unsurprisingly, utmost in our interest here is the detection and mitigation of deepfake imagery and video. "
"We welcome your engagement with our ARIs in the following ways:
• If you have evidence that completely or partly supports or answers one of our ARIs, we invite you to share that with us. For any ongoing research relevant to policing and crime reduction, we encourage you to register your research on the College of Policing’s research projects map, which has been designed to promote collaboration and support requests for participants.
• If you are, or plan to be, carrying out research that relates to one of our ARIs, we’d like to hear about it. While we cannot respond to speculative approaches for research funding, we will where possible act to support your ambitions, including finding you policing partners where possible.
• If you are submitting a funding or grant application that aligns with one of our ARIs, we hope that referencing policing’s ARIs will help to strengthen your case for the possible public impact of the research.
• We will use the ARI document to structure our academic engagement, prioritise events and build new connections with external partners. We will be using our ARIs in our engagement with UKRI, and we will publish any opportunities for funding via our website https://science.police.uk/
Please send any correspondence and questions to csa@npcc.police.uk, including ‘ARI’ in the subject heading."
This question was published as part of the set of ARIs in this document:
Project DEVISIVE uses the very latest advances in machine learning and image processing to address the challenges of synthetic video. Videos that show untruthful imagery of people present a major threat to society, and t...
Funded by: Innovate UK
Lead research organisation: IPROOV RESEARCH LIMITED
The project focuses on detecting synthetic video attacks, which is relevant to the question about counter technologies for audio-visual data processing systems used by the police.