课题基金 / 基金详情

Improving Eye Movement Biometrics Using Remote Registration of Eye Blinking Patterns

Improving Eye Movement Biometrics Using Remote Registration of Eye Blinking Patterns
使用眨眼模式的远程注册改进眼动生物识别技术
批准号:
537769-2018
负责人:
Hatzinakos, Dimitrios
金额:
$0.91万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Plus Grants Program
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

项目摘要

项目成果

Hatzinakos, Dimitrios的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
With increasing integration of advanced technologies into our daily life, the need of reliable biometric**authentication and identification systems is more pronounced than ever before in order to improve security and**privacy and to reduce the risk of circumvention. Despite high accuracy, current biometric technologies relying**on particular physical features such as fingerprints, face and iris characteristics are vulnerable to spoofing and**forgery. Therefore, there is a real need for development of more reliable biometric solutions for human**recognition that are able to continuously identify/authenticate people without requiring specific actions from**them (e.g. placing fingers on an scanner or looking into an iris camera). In a recent NSERC Engage project, we**carried out a feasibility study on human recognition based on remote video capture of eye movements and**blinking. By fusing two biometric modalities that is eye movement (gaze) and eye blinking we were able to**achieve very good results that is up to 95.83% recognition rate and 2.15% error rate. Data were collected in the**University of Toronto Laboratory from 22 volunteers watching carefully selected video sequences. In this**project we will conduct the same experiment with a camera attached to the front of a car's dashboard, facing**towards the driver. As there are different (and changing) lighting conditions and more movements done by the**driver, there may be more outliers and variation in the data that may alter the results. Furthermore, it will test**the theory with practice as the simulated driving results will be put up against a real session. The data collected**would also determine how pragmatic the system is in being non-invasive, as well as how often it can**continuously authenticate the driver- especially in extreme cases. In order to accomplish this task, we plan to**perform experiments using the real life driving simulator available at our industrial partner, ACS corp.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Medical Biometrics Enabled Affective Computing (MBEAC)
  • 批准号:
    RGPIN-2017-06099
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.81万
  • 财政年份:
    2021
  • 负责人:
    Hatzinakos, Dimitrios
  • 依托单位:
Medical Biometrics Enabled Affective Computing (MBEAC)
  • 批准号:
    RGPIN-2017-06099
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2020
  • 负责人:
    Hatzinakos, Dimitrios
  • 依托单位:
Privacy preserving zero-knowledge proof and face recognition
  • 批准号:
    560302-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $1.82万
  • 财政年份:
    2020
  • 负责人:
    Hatzinakos, Dimitrios
  • 依托单位:
Medical Biometrics Enabled Affective Computing (MBEAC)
  • 批准号:
    RGPIN-2017-06099
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.4万
  • 财政年份:
    2019
  • 负责人:
    Hatzinakos, Dimitrios
  • 依托单位:
海外基金