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The authors introduce a new approach to reconstructing accurate camera geometry and 3D models for urban structures in a holistic fashion, i.e., without relying on extraction or matching of traditional local features such as points and edges. Instead, they use semi-global or global features based on transform invariant low-rank textures, which are ubiquitous in urban scenes. Modern high-dimensional optimization techniques enable one to accurately and robustly recover precise and consistent camera calibration and scene geometry from single or multiple images of the scene. They demonstrate how to construct 3D models of large-scale buildings from sequences of multiple large-baseline un-calibrated images that conventional SFM systems do not apply.
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