Improving Eye Movement Biometrics Using Remote Registration of Eye Blinking Patterns
Improving Eye Movement Biometrics Using Remote Registration of Eye Blinking Patterns
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
中文摘要
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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.
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