Cursor Control Based on Eyeball Movement Using Deep Learning

We bring forth the notion of using the eyes to control the computer cursor. Finding a person's gaze point or tracking their eye movement is called eye tracking. Without requiring hardware input, it is feasible to interact with interfaces directly by capturing eye movements and using them as control signals. It aspires to replace the mouse, the piece of hardware most essential for using a computer. In order to classify the individual eyeballs of both human eyes with a high degree of accuracy and control over movement, this system additionally implements a deep learning approach with some built-in data set. For those with restricted mobility, this concept will be quite helpful. Python, OpenCV, NumPy, and a few more facial recognition programs are required software for this method, along with a simple webcam. The HOG (Histogram of Oriented Gradients) is a popular tool for building face detectors.