RESEARCH ON AI TRAFFIC SURVEYS USING CLOSED CIRCUIT TELEVISION SYSTEMS

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  • CCTV映像を用いたAI交通量調査に関する研究

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<p> In vehicle traffic surveys, methods are being proposed to replace the current visual surveys with AI traffic surveys. These AI traffic surveys are utilizing advanced image processing methods more than ever before, and against this background, new vehicle-count methods are being proposed. These methods analyze 4K videos taken by video cameras at survey points, and if these existing methods could be applied to existing CCTV images owned by road managers, it would become possible to conduct AI traffic surveys without the necessity of installing new cameras. However, many CCTV videos have a low resolution because they are intended for long-term monitoring, and in addition, there is a dullness due to image distortion or deterioration due to the long length of time since installation. Therefore, there is a high possibility that the accuracy may be insufficient for traffic volume observation using existing methods. In this research, focusing on the fact that features due to image distortion and dullness can be removed by blurring vehicle images detected from the entire image, a vehicle-type recognition method is proposed using only major features of the vehicles. In a demonstration experiment, we compared the classification accuracy before and after the introduction of the proposed method, and showed that it is possible to count small and large vehicles with higher accuracy than the existing method for SD and HD quality video images. As a result, we were able to confirm the effectiveness of the proposed method in AI traffic volume surveys.</p>

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