Abstract: Virtual gestures that control multimedia playback in order to allow users to interact with the media without having any direct contact with it. Computer vision techniques are applied to a laptop camera in order to detect and interpret hand gestures in real time. Based on Python with OpenCV and MediaPipe, it tracks the hand movements and translates them into actions like play/pause, volume adjustment. Since it does not use deep learning model and rather follows the rules, this process is quick and relatively easy to implement. The functionality is augmented by a trigger-based feature so that gesture recognition is only active when necessary, preventing unnecessary processing and increasing efficiency. It does well in its usual realm with speedy and correct answers. Our method is simple, low-cost and applicable in smart environments and assistive systems when touchless interaction is needed.

Keywords: Gesture Recognition, Human–Computer Interaction, Computer Vision, Multimedia Control, Touchless Interface

Downloads: | DOI: 10.17148/IARJSET.2026.13447