Eye-Tracker to Control Pointer Using Machine Learning

Abstract

Abstract: For preprocessing and analyzing eye-tracking data In an increasingly digital world, human-computer interaction has become a vital aspect of daily life. Traditionalinput devices like mice and touchpads may not be accessible to all individuals, especially those with physicaldisabilities. This project aims to develop an innovative solution to address this issue by creating an eye-tracking- based pointer control system using machine learning techniques. The primary goal of this project is to design and imp element a system that allows users to control a computer's cursor or pointer solely through the movement of their eyes. This will be achieved by leveraging state-of-the-art machine learning algorithms to accurately track and interpret the user's eye movements. we envision a novel eye-tracking-based pointer control system that can enhance the accessibility and usability of computers for diverse range of users. This technology has the potential to empower individuals with disabilities and make computing more intuitive and inclusive for everyone. The front-end involves Html, CSS, and JavaScript which are the fundamental web technologies for creating the userinterfaceand displaying the eye-tracking results. and the backend involves Python. The framework used is Tkinter and OpenCV is used which is a computer vision library thatcan be used