Post-COVID-19 online learning growth has made self-education easier but often ignores human attention spans with static content. HCI solutions like Hand Gesture Recognition with AR and Computer Vision create engaging learning experiences that enhance motor skills, intellectual capacity, and coordination. Our project teaches basic math through finger counting, using instant feedback and gamification to boost interest and learning efficiency, while providing teachers with tools for hands-on, interactive instruction.
This interactive learning platform enhances learning through hand gesture recognition by integrating HCI principles with computer vision.
Dataset Description A webcam-captured hand gesture dataset contains video frames processed by MediaPipe Hands for accurate tracking. The dataset features gestures in multiple orientations and lighting conditions with a stabilization mechanism to detect only deliberate movements. A 100-question bank enables user interaction through hand gestures with text-to-speech support.
