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Forensic Facial Identification using the Fringe P3 brain wave response (EEG-FIT)

Forensic Facial Identification using the Fringe P3 brain wave response (EEG-FIT)
使用 Fringe P3 脑电波反应 (EEG-FIT) 进行法医面部识别
批准号:
104590
负责人:
金额:
$39.38万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

项目摘要

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中文摘要
翻译
"根据目击者证词制作犯罪嫌疑人的面部合成图(通常称为PhotoFIT或EFIT)是世界各地用于协助刑事调查的主要工具。该项目提出了一种全新的方法,以提高准确性和速度来获取此类图像。目前,犯罪的目击者在受过训练的警察操作员的指导下制作合成图像,这一过程通常涉及大量的口头互动。该项目的合作伙伴Visionmetric和肯特大学的霍华德鲍曼教授旨在通过结合他们的专业知识并取得必要的进步来克服当前方法的局限性。其中心思想是向目击者呈现一系列经过计算与嫌疑犯相似的计算机生成图像。EEG(脑电图)用于捕捉增强的脑电波反应,该反应是在对与犯罪分子相似的刺激做出反应时观察到的。这种方法(称为条纹P3方法)已经由肯特大学的鲍曼广泛开发。Visionmetric专注于应用于人脸的机器学习和人工智能方法。他们建议开发快速和强大的迭代过程,用于从P3信号流中生成越来越相关的面部图像,并将其呈现给证人。它直接利用了目击者的正常脑电波活动,避免了目击者和操作员之间的广泛互动。其目的将是表明,可以产生更准确的嫌疑人图像,并在使用现有方法所需的一小部分时间内。"
英文摘要
"The production of facial composites of criminal suspects from eyewitness testimony (commonly known as PhotoFITs or EFITs) is a staple tool used to assist criminal investigations throughout the world. This project proposes a radical, new way of obtaining such images with increased accuracy and speed.At present, eyewitnesses to crime produce composite images under the guidance of a trained police operator and the process generally involves extensive verbal interaction. The process is thus demanding on human resources (taking 1 - 4 hours) and accuracy is quite low.The project partners Visionmetric and Prof Howard Bowman, University of Kent aim to overcome the limitations of current methods by combining their expertise and making the necessary advances. The central idea is to present eyewitnesses to a crime a rapid sequence of computer-generated images calculated to resemble the suspect. EEG (electroencephalography) is used to capture an enhanced brain wave response that is observed in response to stimuli which bear resemblance to the criminal offender. This method (known as the fringe P3 method) has been extensively developed by Bowman at University of Kent. Visionmetric specialise in machine learning and AI methods applied to the human face. They propose to develop fast and robust iterative processes for generating increasingly relevant facial images from the P3 signal stream and presenting these to the witness.This approach is very fast. It directly exploits the normal brainwave activity of the eyewitness and avoids the need for extensive interaction between the witness and operator. The aim will be to show that more accurate images of a suspect can be produced and in a small fraction of the time that is required using existing methods."
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