PolyBuild: An End-to-End Method for Polygonal Building Contour Extraction from High-Resolution Remote Sensing Images
arXiv:2606.08920v1 Announce Type: cross Abstract: Extracting building polygon contours from high-resolution remote sensing images is a fundamental task for various mapping applications. However, the presence of varying imaging conditions and complex building structures, makes automatic contour extraction extremely challenging. Mainstream approaches for building extraction often rely on pixel-level segmentation followed by multiple post-processing steps to produce building contour, which can be computationally intensive and prone to errors. In this paper, we propose an end-to-end method named P
The increasing availability of high-resolution remote sensing imagery combined with advancements in AI methods like end-to-end learning is enabling better automated analysis.
Improved, automated extraction of building contours is fundamental for a wide range of mapping applications, urban planning, disaster response, and infrastructure development.
This end-to-end method potentially streamlines a complex, multi-step process for building contour detection, making it more efficient and less prone to errors.
- · Mapping agencies
- · Urban planners
- · GIS software providers
- · Remote sensing data analytics companies
- · Manual data annotation services
- · Legacy image processing firms
More accurate and faster creation of digital twin models for urban environments.
Enhanced capabilities for automated change detection and infrastructure monitoring at scale.
Potentially enables new forms of geospatial intelligence and services that rely on up-to-date and precise building information.
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Read at arXiv cs.AI