The invention discloses a traffic jam condition evaluation method, which adopts an advanced video image segmentation technology SAM2, and aims to extract the coverage area of vehicles in a traffic scene video picture by combining a visual segmentation large model SAM2. Therefore, the visual segmentation area mask of the traffic target vehicle can be more accurately obtained in a traffic jam analysis scene, and the traffic density can be more intuitively measured. Meanwhile, the area proportion of the vehicle mask area in the background mask area of the traffic vehicle circulation area is adopted in the assessment of the traffic jam condition, and the comprehensive overall assessment is carried out by combining the factors such as the vehicle mask offset and the time length, so that the comprehensive traffic jam condition can be measured more accurately and effectively.
本申请公开了一种交通拥堵状况评估方法,该评估方法采用了先进的视频图像分割技术SAM2,旨在通过结合视觉分割大模型SAM2抽取交通场景视频画面中车辆的覆盖面积,以使能够在交通拥堵分析场景中更精准地得到交通目标车辆的视觉分割区域掩码,能够更直观地衡量交通密度。同时,在交通拥堵状况的评估中采用了基于车辆掩码区域在交通车辆流通区域背景掩码区域中的面积占比,并结合了车辆掩码偏移及时长等因素进行综合整体评估,从而能够更精确有效地衡量交通的综合拥堵状况。
Traffic jam condition evaluation method, equipment and medium
交通拥堵状况评估方法、设备及介质
2025-03-25
Patent
Electronic Resource
Chinese
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