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

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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.