INTUITIVE GESTURE-DRIVEN AUGMENTED REALITY FOR USER INTERACTION IN LOW-COST AR SYSTEMS - Muhammad-Bello, Bilkisu Larai; Ndubuisi, Awoke Victor; Suleiman, Muhammad Aliyu; Salihu, Ibrahim Anka (FUDMA JOURNAL OF SCIENCES, 2025)
Augmented Reality (AR) offers promising applications in education, healthcare, and industry, but its adoption in low-resource settings is hindered by expensive hardware and complex interaction methods. This study presents a lightweight, gesture-driven AR interface designed to enable intuitive user interaction on low-cost devices. Using standard webcams and open-source tools, MediaPipe for hand landmark detection and OpenCV for visual overlays, a rule-based system was developed to recognize three core gestures (open palm, fist, point) and trigger real-time AR overlays. The system was optimized for latency and frame rate, achieving 81.8% accuracy in gesture recognition during user testing with 20 participants. Real-time performance averaged 44.8 ms latency and 24.6 FPS, demonstrating responsive feedback on entry-level hardware. Despite limitations such as variable lighting and lack of depth sensing, the system proved intuitive and effective for immersive interaction. This work contributes a scalable AR interaction model that enhances accessibility in educational and low-cost environments.