Seat Belt Detection by Road Cameras: Technology and Challenges

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Seat Belt Detection by Road Cameras: Technology and Challenges

Read More: Link 1 - https://www.mdpi.com/2076-3417/14/8/3346 [https://www.mdpi.com/2076-3417/14/8/3346] Link 2 - https://recognito.vision/real-time-seatbelt-monitoring-a-comprehensive-analysis/ [https://recognito.vision/real-time-seatbelt-monitoring-a-comprehensive-analysis/] Discussing advanced technologies used in road cameras for seat belt detection, primarily focusing on computer vision and artificial intelligence systems. These systems employ YOLO networks and Convolutional Neural Networks (CNNs) to analyze images and identify seat belts, even when their color matches clothing. To overcome challenges like color matching, multi-modal detection approaches are utilized, including infrared imaging, edge and shape detection, and texture analysis. Despite achieving 90-95% accuracy, limitations such as false positives, occlusion, and varying lighting conditions persist, which are being addressed through robust training datasets and multi-sensor integration.