Development Of Eye Gaze Estimation System Using Two Cameras

Eye Gaze is the direction where a person is looking at. It is suitable to be used as a type of natural Human Computer Interface (HCI). Current researches uses infrared or LED to locate the iris of the user to have better gaze estimation accuracy compared to researches that does not. Infrared and LED are intrusive to human eyes and might cause damage to the cornea and the retina of the eye. This research suggests a non-intrusive approach to locate the iris of the user. By using two remote cameras to capture the images of the user, a better accuracy gaze estimation system can be achieved. The system uses Haar cascade algorithms to detect the face and eye regions. The iris detection uses Hough Circle Transform algorithm to locate the position of the iris, which is critical for the gaze estimation calculation. To enable the system to track the eye and the iris location of the user in real time, the system uses CAMshift (Continuously Adaptive Meanshift) to track the eye and iris of the user. The parameters of the eye and iris are then collected and are used to calculate the gaze direction of the user. The left and right camera achieves 70.00% and 74.67% accuracy respectively. When two cameras are used to estimate the gaze direction, 88.67% accuracy is achieved. This shows that by using two cameras, the accuracy of gaze estimation is improved

Design of an embedded iris recognition system for use with a multi-factor authentication system.

This paper describes in detail the design, manufacturing and testing of an embedded iris scanner for use with a multifactor authentication system. The design process for this project included hardware design from part selection to board design to populating. Additionally, this process included the entirety of the software development, though the iris recognition process was largely based on other works. The functional requirements for the overall multi-factor authentication system were to have three authentication methods with a thirty second window to complete all three. The system acceptance accuracy was required to be greater than 75%. Those requirements therefore dictate that the iris scanner module must also have an acceptance accuracy higher than 75% and perform iris recognition in a few seconds so that the user can gain admittance in the allotted window of time. While the hardware has been verified and tested, further development and testing is necessary on the software and image processing. This work is funded by the Department of Energy’s Kansas City National Security Campus, operated by Honeywell Federal Manufacturing & Technologies, LLC under contract number DE-NA0002839

A Framework to Detect Presentation Attacks

Biometric-based authentication systems are becoming the preferred choice to replace password-based authentication systems. Among several variations of biometrics (e.g., face, eye, fingerprint), iris-based authentication is commonly used in every day applications. In iris-based authentication systems, iris images from legitimate users are captured and certain features are extracted to be used for matching during the authentication process. Literature works suggest that iris-based authentication systems can be subject to presentation attacks where an attacker obtains printed copy of the victim’s eye image and displays it in front of an authentication system to gain unauthorized access. Such attacks can be performed by displaying static eye images on mobile devices or iPad (known as screen attacks). As iris features are not changed, once an iris feature is compromised, it is hard to avoid this type of attack. Existing approaches relying on static features of the iris are not suitable to prevent presentation attacks. Feature from live Iris (or liveness detection) is a promising approach. Further, additional layer of security from iris feature can enable hardening the security of authentication system that existing works do not address. To address these limitations, this thesis proposed iris signature generation based on the area between the pupil and the cornea . Our approach relies on capturing iris images using near infrared light. We train two classifiers to capture the area between the pupil and the cornea. The image of iris is then stored in the database. This approach generates a QR code from the iris. The code acts as a password (additional layer of security) and a user is iii required to provide it during authentication. The approach has been tested using samples obtained from publicly available iris database. The initial results show that the proposed approach has lower false positive and false negative rates

Distributed Real-Time Computation of the Point of Gaze

This paper presents a minimally intrusive real-time gaze-tracking prototype to be used in several scenarios, including a laboratory stall and an in-vehicle system. The system requires specific infrared illumination to allow it to work with variable light conditions. However, it is minimally intrusive due to the use of a carefully configured switched infrared LED array. Although the perceived level of illumination generated by this array is high, it is achieved using low-emission infrared light beams. Accuracy is achieved through a precise estimate of the center of the user's pupil. To overcome inherent time restrictions while using low-cost processors, its main image-processing algorithm has been distributed over four main computing tasks. This structure not only enables good performance, but also simplifies the task of experimenting with alternative computationally-complex algorithms and with alternative tracking models based on locating both user eyes and several cameras to improve user mobility