Abstract
Background Artificial Intelligence (AI) has the potential to significantly enhance human-computer interactions. This paper introduces a cutting-edge method for computer control using eye-gesture recognition. Methods Our system employs a sophisticated algorithm to accurately interpret eye movements, converting them into actionable commands. This technology not only improves accessibility for individuals with physical impairments, but also offers a more intuitive interaction mode for the general user base. Results We tested our method using a comprehensive dataset and achieved a remarkable accuracy rate of over 99.6283% in translating eye gestures into functional commands. Our system utilizes a variety of tools, including PyCharm, OpenCV, mediapipe, and pyautogui, to achieve these results. Conclusions We discuss potential applications of our technology, such as in the emerging field of gesture-controlled weaponry, which could have significant implications for military and rescue operations. Overall, our work represents a substantial step forward in integrating AI with human-computer interaction, enhancing accessibility, improving user engagement, and unlocking innovative applications for critical industries.
Reference60 articles.
1. Mobile device for electronic eye gesture recognition.;M Kirbis;IEEE Trans. Consum. Electron.,November 2009
2. Eye-gesture controlled intelligent wheelchair using Electro-Oculography.;T Pingali;2014 IEEE International Symposium on Circuits and Systems (ISCAS), Melbourne, VIC, Australia.,2014
3. Spintronic Sensors Based on Magnetic Tunnel Junctions for Wireless Eye Movement Gesture Control.;A Tanwear;IEEE Trans. Biomed. Circuits Syst.,Dec. 2020
4. Head and Eye Egocentric Gesture Recognition for Human-Robot Interaction Using Eyewear Cameras.;J Marina-Miranda;IEEE Robot. Autom. Lett.,July 2022
5. A wireless EOG-based Human Computer Interface.;M Lin;2010 3rd International Conference on Biomedical Engineering and Informatics, Yantai, China.,2010