Geometric approximation of urban objects with compact and accurate representation is a challenging problem that concerns both computer vision and computer graphics communities. Existing literature mainly focuses on reconstruction from high-quality point clouds obtained by laser scanning which are too costly for many practical scenarios. This...
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October 8, 2021 (v1)PublicationUploaded on: December 3, 2022
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2021 (v1)Conference paper
We present a global registration algorithm for multi-modal geometric data, typically 3D point clouds and meshes. Existing feature-based methods and recent deep learning based approaches typically rely upon point-to-point matching strategies that often fail to deliver accurate results from defect-laden data. In contrast, we reason at the scale...
Uploaded on: December 4, 2022 -
June 14, 2020 (v1)Conference paper
We present an algorithm for extracting and vectorizing objects in images with polygons. Departing from a polygonal partition that oversegments an image into convex cells, the algorithm refines the geometry of the partition while labeling its cells by a semantic class. The result is a set of polygons, each capturing an object in the image. The...
Uploaded on: December 4, 2022 -
September 9, 2019 (v1)Conference paper
Recent years have seen an explosion of the number of camera modules integratedinto individual consumer mobile devices, including configurations that contain multi-ple different types of image sensors. One popular configuration is to combine an RGBcamera for color imaging with a monochrome camera that has improved performancein low-light...
Uploaded on: December 4, 2022