Vision Sense: Real-Time Object Detection And Audio Feedback System For Visually Impaired Individuals

被引:0
|
作者
Chinni, Naga Praneeth Kumar [1 ]
Kaamaala, Sai Pranav Reddy [1 ]
Vardhan, Bhasham Vishva [1 ]
Kishan, Adari Uday [1 ]
Richards, Vasimalla Sunny [1 ]
Vardhan, Ramadasu Nooka Harsh [1 ]
Puneet [1 ]
机构
[1] Lovely Profess Univ, Comp Sci & Engn, Jalandhar, Punjab, India
来源
2024 2ND WORLD CONFERENCE ON COMMUNICATION & COMPUTING, WCONF 2024 | 2024年
关键词
YOLO model; COCO dataset; object detection; visually impaired assistance; real-time processing; audio feedback; computer vision; assistive technology;
D O I
10.1109/WCONF61366.2024.10692302
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This project introduces a transformative object detection system designed to enhance the navigational capabilities of visually impaired individuals through the application of advanced computer vision technologies. Utilizing the You Only Look Once (YOLO) model, paired with the Comprehensive Object Collection (COCO) dataset, this system provides real-time, accurate object detection and classification. The core functionality of the application allows for the processing of both static images and live video feeds, enabling blind users to receive auditory announcements of nearby objects, thereby assisting with spatial awareness and environmental interaction. The system leverages a pre-trained YOLO model to ensure robust detection performance, achieving a peak detection accuracy of 99%. By delivering object labels and bounding box coordinates audibly, the application serves as a critical tool in improving the daily independence and quality of life for people with visual impairments. This project not only highlights the potential of deep learning in assistive technologies but also underscores the importance of adaptive solutions in inclusive technology development.
引用
收藏
页数:6
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