Non-intrusive Eye Gaze Estimation from a System with Two Remote Cameras
Yu Zun Neoh1, Haidi Ibrahim2
1Yu Zun Neoh, School of Electrical & Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, Seberang Perai Selatan, Penang, Malaysia.
2Haidi Ibrahim, School of Electrical & Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, Nibong Tebal, Seberang Perai Selatan, Penang, Malaysia.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 2666-2674 | Volume-8 Issue-7, May 2019 | Retrieval Number: G5876058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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 use 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.
Keyword: Eye Gaze, Human Computer Interaction, Iris Detection, two Cameras System.
Scope of the Article: Remote Sensing