Real Time Object Detection And Audio Feedback For Visually Impaired
Keywords:
YOLOAbstract
This project presents a real-time object detection system integrated with audio feedback designed to assist visually impaired individuals in navigating their environment safely and independently. The system utilizes a combination of computer vision and deep learning algorithms to identify objects in the user's surroundings through a live camera feed. Upon detecting objects, the system provides immediate audio cues describing the identified items and their relative position, enhancing the user’s situational awareness. The solution is implemented using technologies such as OpenCV, TensorFlow (or YOLO), and a text-tospeech engine, all optimized for real-time performance on portable hardware like Raspberry Pi or mobile devices. This assistive technology aims to bridge the gap between visual impairment and spatial perception, offering an affordable, effective, and user-friendly aid for daily life navigation.
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References
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