Hand Gesture Recognition for Video Player

Abstract

Hand Gesture Recognition (HGR) is an emerging technology that has numerous applications in various fields, including human-computer interaction and robotics. In this project, we developed a Hand Gesture Recognition system for video players that recognize hand gestures and perform actions such as play, pause, rewind, and fast-forward. The system was developed using Python programming language and the OpenCV, mediapipe, pyautogui libraries. A dataset of hand gestures was created by recording videos using a webcam and annotating the frames with corresponding labels. The Hand Gesture Recognition system achieved an accuracy of 92% on the test set and was able to accurately recognize hand gestures and perform the corresponding actions on a video player. The system has the potential to be used as a novel way to control video players, especially in situations where the user cannot use a mouse or keyboard. In conclusion, the Hand Gesture Recognition system developed in this project provides a promising solution for controlling video players using hand gestures. The system achieved a high level of accuracy in recognizing gestures and performing actions, and can potentially be used in a variety of applications. Further improvements and refinements can be made to the system in the future to make it even more effective and user- friendly.