A Perceptual Scaling Approach to Eyewitness Identification

目击者识别的感知尺度方法

• 批准号: 2044092
• 负责人: Thomas Albright
• 金额: $ 50万
• 依托单位: The Salk Institute for Biological Studies
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2024-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2044092&HistoricalAwards=false
• 关键词: Perceptual; Scaling; Approach; Eyewitness; Identification

Eyewitness identification has long played an important role in criminal investigations and prosecutions, where identifying the culprit is critical to the criminal justice process. Based on advances in understanding of perception and memory, this project will examine the role of “fillers” in lineups. Fillers are the individuals in a lineup known to be innocent who serve to challenge eyewitness recognition. The research will develop a novel method for filler selection based on a combination of human and machine measures of facial similarity.The project builds upon a new paradigm for the design and conduct of lineups for eyewitness identification. Drawing upon perceptual scaling, well-established in sensory psychology, this approach will be used to estimate the strength of eyewitness memories, and thus to generate large libraries of facial images in which the degree of facial similarity is quantified. This research will help to reduce susceptibility of the eyewitness to decision bias and will provide quantitative measures of the perceived similarity of faces. These measures, in combination with a machine learning algorithm, will be used to create a model witness, which is an algorithm that reproduces similarity judgements of human observers and predicts perceptual similarity for new faces. The project will yield an objective system for selecting fillers in order to optimize eyewitness fairness and performance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

目击者的身份长期以来一直在刑事调查和起诉中发挥了重要作用，在刑事调查和起诉中，确定罪魁祸首对于刑事司法程序至关重要。基于对感知和记忆的理解的进步，该项目将研究“填充”在阵容中的作用。填充物是众所周知的无辜者阵容中的个人，他们有助于挑战目击者的认可。该研究将根据人体相似性的组合开发一种新的方法来选择填充物。该项目基于设计和行为的目击者识别阵容的新范式。利用感知缩放，在感觉心理学方面建立了良好的缩放，该方法将用于估计目击者记忆的强度，从而产生大型面部图像库，其中量化面部相似性程度。这项研究将有助于降低目击者对决策偏见的敏感性，并将提供对面部相似性相似性的定量测量。这些措施与机器学习算法结合使用，将用于创建模型证人，该算法是一种算法，可再现人类观察者的相似性判断，并预测新面孔的知觉相似性。该项目将产生一个客观的系统来选择填充物，以优化目击者的公平性和性能。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估标准通过评估来支持的。