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Human Recognition based on Remote Video Capture of Eye Movements and Blinking

基于眼球运动和眨眼的远程视频捕捉的人体识别

基本信息

批准号：
517520-2017
负责人：
Hatzinakos, Dimitrios
金额：
$ 1.82万
依托单位：
University of Toronto
依托单位国家：
加拿大
项目类别：
Engage Grants Program
财政年份：
2017
资助国家：
加拿大
起止时间：
2017-01-01 至 2018-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640040
关键词：
Human Recognition based Remote Video

项目摘要

With increasing integration of advanced technologies into our daily life, the need of reliable biometricauthentication and identification systems is more pronounced than ever before in order to improve security andprivacy and to reduce the risk of circumvention. Despite high accuracy, current biometric technologies relyingon particular physical features such as fingerprints, face and iris characteristics are vulnerable to spoofing andforgery. Therefore, there is a real need for development of more reliable biometric solutions for humanrecognition that are able to continuously identify/authenticate people without requiring specific actions fromthem (e.g. placing fingers on an scanner or looking into an iris camera). In this project, we propose a feasibilitystudy on human recognition based on remote video capture of eye movements and blinking. The proposedsolution based on eye tracking data offers a more flexible design, where eye movement and blinking patternsare captured on video recordings taken from greater distance which is non-intrusive, simpler to analyze andmore difficult to spoof. Furthermore, it offers an added advantage where the same features extracted forbiometric recognition can be used for determining fatigue or other physiological conditions or behavioralchanges.

随着先进技术日益融入我们的日常生活，对可靠的生物特征认证和识别系统的需求比以往任何时候都更加突出，以提高安全性和隐私性，并减少规避风险。尽管准确性很高，但目前的生物识别技术依赖于特定的物理特征，如指纹，面部和虹膜特征，很容易受到欺骗和伪造。因此，真实的需要开发用于人类识别的更可靠的生物识别解决方案，其能够连续地识别/认证人而不需要他们的特定动作（例如，将手指放在扫描仪上或看着虹膜相机）。在这个项目中，我们提出了一个可行性研究的基础上，远程视频捕获的眼睛运动和眨眼的人识别。基于眼动追踪数据的解决方案提供了一个更灵活的设计，其中眼睛运动和眨眼模式被捕获在从更远距离拍摄的视频记录上，这是非侵入性的，更容易分析，更难以欺骗。此外，它还提供了一个额外的优势，其中为生物识别提取的相同特征可以用于确定疲劳或其他生理状况或行为变化。