Detection and Tracking of Walking Pedestrians in Smart Transportation System Videos
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In intelligent transportation systems, video surveillance technology has become a crucial component. The development of walking pedestrian detection and tracking technology holds significant importance. This technology primarily utilizes computer vision techniques to automatically identify, detect, and track pedestrians in video streams, enabling real-time monitoring and analysis of pedestrian behavior. Implementation typically involves background subtraction algorithms for motion detection, coupled with machine learning classifiers like HOG-SVM or YOLO for pedestrian recognition. Tracking mechanisms often employ Kalman filters or correlation filters to maintain pedestrian trajectories across frames. Such technological solutions can reduce traffic accidents, enhance urban traffic management efficiency, and contribute substantially to urban safety and infrastructure development.
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