Ground Plane Projection for Improved Traffic Analytics at Intersections
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Abstract (arXiv)
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
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 9 of its 39 references that are in the map. First posted on arXiv 15 Nov 2025.
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9 of 39 references.
References · 9
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- 2021The 5th AI City Challengecited by 28
- 2022The 6th AI City Challengecited by 23
- 2020The 4th AI City Challengecited by 18
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Citing papers per year: 2026: 1.
1 paper.