Technical Papers Session III: Optical assistance for Motor Neuron Disease (MND) patients using real-time eye tracking
Abstract/Description
Face detection and eyes extraction has an important role in many applications such as face recognition, facial expression analysis, security login etc. The system is designed to develop an eye-motion based communication system for patients suffering from motor neuron disease (MND) to contact with care takers whenever they want. In this paper, we proposed a method to efficiently track eye gaze detection in real time from video acquired by a web camera. The camera is stationary with respect to the head. Proposed system is mainly divided into three steps; face detection, eye-ball(pupil) detection and finally eye gaze detection. Using predefined facial landmarks face is detected in real time. Then in the second step face point that were extracted in phase one helps to detect eye point and using circular Hough Transform eye pupil was accurately detected. Finally, in the last stage eye gaze was calculated using gaze ratio formula. The experiments are conducted on people from different age groups and a high accuracy rate is achieved.
Location
Room C9 (Aman Tower, 3rd floor)
Session Theme
Technical Papers Session III - Computer Vision
Session Type
Parallel Technical Session
Session Chair
Dr. Asim Ur Rehman Khan
Start Date
16-11-2019 2:30 PM
End Date
16-11-2019 2:50 PM
Recommended Citation
Aslam, Z., Junejo, A. Z., Memon, A., Raza, A., Aslam, J., & Thebo, L. A. (2019). Technical Papers Session III: Optical assistance for Motor Neuron Disease (MND) patients using real-time eye tracking. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2019/2019/15
COinS
Technical Papers Session III: Optical assistance for Motor Neuron Disease (MND) patients using real-time eye tracking
Room C9 (Aman Tower, 3rd floor)
Face detection and eyes extraction has an important role in many applications such as face recognition, facial expression analysis, security login etc. The system is designed to develop an eye-motion based communication system for patients suffering from motor neuron disease (MND) to contact with care takers whenever they want. In this paper, we proposed a method to efficiently track eye gaze detection in real time from video acquired by a web camera. The camera is stationary with respect to the head. Proposed system is mainly divided into three steps; face detection, eye-ball(pupil) detection and finally eye gaze detection. Using predefined facial landmarks face is detected in real time. Then in the second step face point that were extracted in phase one helps to detect eye point and using circular Hough Transform eye pupil was accurately detected. Finally, in the last stage eye gaze was calculated using gaze ratio formula. The experiments are conducted on people from different age groups and a high accuracy rate is achieved.
