Virtual navigation controls system and object detection using computer vision

Abstract

The Virtual Navigation Control and Object Detection System is a solution designed to provide users with virtual navigation tools and real-time object detection capabilities using computer vision. Leveraging the device's camera, the system enables hands-free control through gesture recognition, eliminating the need for physical peripherals. Advanced object detection offers users immediate information about their surroundings, enhancing user experience, accessibility, and educational opportunities. Key technologies include computer vision libraries, machine learning algorithms, and a user- centered interface. Testing demonstrated over 95% accuracy in gesture recognition and 92% accuracy in object detection under normal lighting (85% in low-light conditions). Integration tests confirmed smooth communication between modules, with real-time operation averaging a 0.2-second response time. The system's scalability allows for handling multiple objects and complex gestures, though further refinement may enhance its performance in diverse environments. These results indicate substantial progress toward an accessible, reliable, and secure alternative to traditional input methods. Potential applications include healthcare, where hands-free control improves hygiene, and accessibility aids for visually impaired users, highlighting the system's broad applicability in enhancing human-computer interaction.