将车辆检测结果投影到地面平面，提升路口转向行为分析精度
Ground Plane Projection for Improved Traffic Analytics at Intersections
- 将图像中检测的车辆反投影至真实三维地面坐标系分析
- 单相机系统下轨迹分类与转向计数准确率显著提升
- 多相机弱融合进一步提高精度，适合智能交通系统应用
路口转弯行为的精准统计对信号控制、交通管理与城市规划至关重要。当前基于基础设施摄像头的计算机视觉系统通常在图像平面上进行视觉分析。本文探索将一个或多个摄像头检测到的车辆反投影至地面平面，在真实三维坐标系中进行分析的潜在优势。结果显示，单相机系统中反投影可显著提升轨迹分类与转向行为计数的准确性；进一步通过多相机反投影检测的弱融合，可实现更高精度。结果表明，交通分析应基于地面平面而非图像平面。
原文摘要 · Abstract (English)
Accurate turning movement counts at intersections are important for signal control, traffic management and urban planning. Computer vision systems for automatic turning movement counts typically rely on visual analysis in the image plane of an infrastructure camera. Here we explore potential advantages of back-projecting vehicles detected in one or more infrastructure cameras to the ground plane for analysis in real-world 3D coordinates. For single-camera systems we find that back-projection yields more accurate trajectory classification and turning movement counts. We further show that even higher accuracy can be achieved through weak fusion of back-projected detections from multiple cameras. These results suggeest that traffic should be analyzed on the ground plane, not the image plane
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