Increasing eyewitness identification accuracy in lineups using 3D interactive virtual reality

使用 3D 交互式虚拟现实提高阵容中目击者识别的准确性

• 批准号: ES/X010740/1
• 负责人: Heather Flowe
• 金额: $ 62.18万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FX010740%2F1
• 关键词: Increasing; eyewitness; identification; accuracy; lineups

Accurate witness identification (ID) is a cornerstone of police inquiries and national security investigations. Yet, the technology used to display lineups has not fundamentally changed over the past century. Worldwide, police present witnesses with 2D photographic lineups. Eyewitnesses often err on ID tests-analyses of real-world police identification parades reveal that witnesses quite often identify known-innocent suspects as culprits. Eyewitness mistakes can have dire consequences and been implicated in about 70% of wrongful convictions. This project implements recent advances in 3D image technology and virtual reality (VR) to increase witness ID accuracy. We will develop a new lineup procedure that enables witnesses to rotate 3D faces and view them moving into different angles in VR. Our project brings together an international team of academics and practitioners from the United Kingdom (University of Birmingham, University of Stirling), Canada (University of Victoria), and Germany (the Max Planck Institute for Human Cognitive and Brain Sciences, and Humboldt-Universität zu Berlin). The researchers are among the best in their fields and have the necessary and unique expertise to develop the interactive 3D VR lineup system. Our cross-national approach will allow for robust testing and external validation by a wide range of end users. Our objectives are as follows: 1) develop novel methods for the creation of 3D representations of human faces that allow for editing and adaptation of appearance properties (e.g., expressions, lighting) as well as methods for photorealistic (neural) rendering in VR; 2) conduct laboratory experiments to establish the advantage of interactive 3D VR lineups over 2D lineups, as well as active over passive face exploration; 3) test the effect of different types of retrieval cues (e.g., vertical movement, facial expressions, lighting) on accuracy and reliability; 4) identify the individual difference characteristics (e.g., face processing ability, engagement with interactive 3D VR lineups) associated with performance in lineups; 5) explore the relationships between individual differences in face processing ability and lineup performance (e.g., discrimination accuracy) and model face processing in 2D and 3D tasks; and 6) present results to police practitioners to develop policy and practice recommendations for the implementation of interactive 3D VR lineups in a range of criminal justice contexts. In sum, our project combines theory and state-of-the art computing skills of the leading experts in their respective fields to substantially improve lineup procedures in applied settings.

准确的证人身份（ID）是警察调查和国家安全调查的基石。然而，在过去的一个世纪中，用于展示阵容的技术并没有从根本上发生变化。全球，警察为目击者展示了2D摄影阵容。目击者通常会在ID测试中犯错 - 现实世界警察识别游行的Analyses表明，证人经常将已知的无罪嫌疑人确定为罪魁祸首。目击者的错误可能会带来不利的后果，并在大约70％的错误定罪中实施。该项目实现了3D图像技术和虚拟现实（VR）的最新进展，以提高证人ID的准确性。我们将开发一个新的阵容程序，使证人能够旋转3D面并查看他们在VR中移动到不同角度。我们的项目汇集了来自英国（伯明翰大学，斯特林大学），加拿大（维多利亚大学）和德国（Max Planck人类认知和脑科学研究所，洪堡 - UniversitätZu Zu berlin）的国际学者和从业人员。研究人员是他们领域中最好的研究人员之一，并且具有开发交互式3D VR系列系统的必要和独特专业知识。我们的跨国方法将允许广泛的最终用户进行强大的测试和外部验证。我们的目标如下：1）开发新的方法来创建人面部的3D表示，从而可以编辑和适应外观特性（例如表达式，照明）以及在VR中呈现的光真逼真（神经）渲染的方法； 2）进行实验室实验，以确定与2D阵容相比的交互式3D VR阵容的优势，并在被动面部探索中积极主动； 3）测试不同类型的检索提示（例如垂直运动，面部表情，照明）对准确性和可靠性的影响； 4）确定与阵容中的性能相关的个体差异特征（例如，面部处理能力，与交互式3D VR阵容的参与）； 5）探索面部处理能力和阵容性能（例如歧视精度）的个体差异与2D和3D任务中的模型面部处理之间的关系； 6）为警察实践者提供结果，以制定政策和实践建议，以在一系列刑事司法背景下实施互动3D VR阵容。总而言之，我们的项目结合了各个领域领先专家的理论和最先进的计算技能，以实质上改善了应用环境中的阵容程序。