학술논문

Mimicking 2-DOF Human Eye Movement using an IR Camera-Based Wearable Eye-Gaze Tracking Controller
Document Type
Conference
Source
2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI) Advances in Electrical, Electronics and Computational Intelligence (ICAEECI), 2023 First International Conference on. :1-6 Oct, 2023
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Head
Tracking
Wearable computers
Robot vision systems
2-DOF
Gaze tracking
Cameras
wearable controller
wearable
eye tracker
eye-gaze tracking
IR
PCCR
head compensation
corneal reflection
convergence error
mimicking
Language
Abstract
This study presents the real-time human-robot mimicry of the human eye two degrees-of-freedom (2-DOF) movements. The control system uses an IR camera-based wearable eye-gaze tracking controller attached to the human head to control the robotic eye. Building upon previous studies, this study addresses limitations of existing eye gaze tracking systems for robotic control in horizontal and vertical eye movements including attempts to compensate for head movements using a wearable controller. The researchers employ image processing through IR camera in eye-gaze tracking system in the wearable controller, applying the Pupil Center Corneal Reflection (PCCR) concept and polynomial regression that enables to replicates the eye movements made by humans into the robotic eye. After a statistical analysis done in the data gathered through Wilcoxon Test, the p-values obtained for horizontal and vertical movements are higher than the alpha level. This means that the observations indicate no statistically significant difference between the angles of the human eye and the robotic eye. The results demonstrate that the wearable eye-gaze tracking controller’s control system allows the robotic eye to mimic human eye movements, with a highly accurate horizontal movement of 99.07% and vertical movement of 98.91%, resulting in an overall accuracy of 98.99% in mimicking human eye movements.