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) 是警方调查和国家安全调查的基石，然而，在过去的一个世纪里，用于显示证人名单的技术并没有发生根本性的变化，警方向证人提供 2D 照片证人身份测试时经常出错。 - 对现实世界警察辨认游行的分析表明，目击者经常将已知无辜的嫌疑人识别为罪犯。 70% 的错误定罪。该项目采用了 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。我们将开发一种新的排队程序，使证人能够旋转 3D 面孔并在 VR 中观看他们移动到不同的角度。我们的项目汇集了来自英国（伯明翰大学、斯特灵大学）、加拿大（维多利亚大学）和德国（马克斯·普朗克人类认知和脑科学研究所，以及柏林洪堡大学的研究人员是各自领域的佼佼者，拥有开发交互式 3D VR 阵容系统所需的独特专业知识，我们的跨国方法将允许广泛的测试和外部验证。我们的目标如下：1）开发用于创建人脸 3D 表示的新颖方法，允许编辑和调整外观属性（例如表情、光照）以及照片级真实感（神经）渲染方法。 VR 领域；2) 进行实验室实验，以确定交互式 3D VR 阵容相对于 2D 阵容的优势，以及主动面部探索相对于被动面部探索的优势；3) 测试不同类型检索线索的效果（例如，垂直运动、面部表情、照明）的准确性和可靠性；4）识别与阵容表现相关的个体差异特征（例如，面部处理能力、对交互式 3D VR 阵容的参与度）；5）探索个体差异之间的关系；人脸处理能力和阵容性能（例如，辨别准确性）以及 2D 和 3D 任务中的模型人脸处理；以及 6) 向警察从业人员提供结果，以便为在一系列刑事司法中实施交互式 3D VR 阵容制定政策和实践建议总之，我们的项目结合了各自领域领先专家的理论和最先进的计算技能，以显着改进应用环境中的阵容程序。