THE RESEARCH
Overview of the Research
The 3D Interactive Lineups (3DIL) project is dedicated to enhancing eyewitness identification accuracy through cutting-edge 3D virtual reality (VR) technology. Traditional 2D photo lineups often fail to capture the complexity of real-life face recognition, leading to mistaken identifications and potential wrongful convictions. The 3DIL project aims to develop interactive 3D lineups, allowing witnesses to view lifelike facial models from multiple angles, increasing the realism and reliability of identifications.
The research involves a cross-national team from the UK, Germany, and Canada, combining expertise in psychology, computer science, and law enforcement practices. Our collaborative approach ensures robust testing and practical relevance across different legal systems and cultural contexts.
RESEARCH OBJECTIVES
Create realistic, editable 3D facial models using advanced rendering techniques, allowing for adjustments in facial appearance, lighting, and expressions.
Conduct experiments to evaluate the effectiveness of 3D interactive lineups compared to traditional 2D methods.
Analyse how different retrieval cues, such as facial movements and lighting changes, impact the accuracy of witness identifications.
Study how individual differences in cognitive abilities, such as face recognition skills, influence lineup performance.
Explore the relationship between face processing abilities and identification accuracy to develop predictive models of eyewitness performance.
Collaborate with law enforcement to create guidelines and best practices for the implementation of 3D VR lineups in real-world settings.
Associated Outputs
Barthel, F., Hilsmann, A., and Eisert, P. (2024). Multi-view Inversion for 3D-aware Generative Adversarial Networks
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Colloff, M. F., et al. (2022). Active exploration of faces in police lineups increases discrimination accuracy for own- and other- race faces. American Psychologist.
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Flowe, H. D., Carline, A., & Karoğlu, N. (2018). Testing the Reflection Assumption: A Comparison of Eyewitness Ecology in the Laboratory and Criminal Cases. International Journal of Evidence and Proof, 22, 239–261.
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Smith, H. M. J., Andrews, S., Baguley, T. S., Colloff, M. F., Davis, J. P., White, D. & Flowe, H. D. (2021). Performance of Typical and Superior Face Recognisers on a Novel Interactive Face Matching Procedure. British Journal of Psychology.
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Barthel, F., Hilsmann, A., and Eisert, P. (2024). Multi-view Inversion for 3D-aware Generative Adversarial Networks
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Colloff, M. F., et al. (In press). Active exploration of faces in police lineups increases discrimination accuracy for own- and other- race faces. American Psychologist.
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Flowe, H. D., Carline, A., & Karoğlu, N. (2018). Testing the Reflection Assumption: A Comparison of Eyewitness Ecology in the Laboratory and Criminal Cases. International Journal of Evidence and Proof, 22, 239–261.
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Smith, H. M. J., Andrews, S., Baguley, T. S., Colloff, M. F., Davis, J. P., White, D. & Flowe, H. D. (In press). Performance of Typical and Superior Face Recognisers on a Novel Interactive Face Matching Procedure. British Journal of Psychology.
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Mickes, L., *Seale-Carlisle, T., Colloff, M., Wells, W., Flowe, H. (2019). Confidence and response time as indicators of eyewitness identification accuracy in the lab and in the real world. Journal of Applied Research in Memory and Cognition.
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