Abstract: A virtual interaction system is developed utilizing computer vision techniques through the OpenCV library in Python to reduce dependency on conventional input devices. The system enables seamless user interaction using hand gestures and facial identification, providing a contactless and built in human-computer interface. Core functionalities include a virtual mouse for cursor control, an air canvas for gesture-based drawing, a background replacement module, and gesture-controlled PowerPoint navigation. Live video input is processed via a webcam use Haar Cascade Classifiers, motion tracking follow, and feature extraction techniques to detect and interpret user gestures. The system aims to enhance accessibility, interactivity, and ease of use in various computing environments by offering a non-invasive alternative to traditional input methods.

Keywords: Computer Vision, OpenCV, Gesture Recognition, Virtual Mouse, Air Canvas, Background Substitution.

| DOI: 10.17148/IARJSET.2025.125273