Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
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The digital Michelangelo project: 3D scanning of large statues
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Proceedings of the 28th annual conference on Computer graphics and interactive techniques
New Techniques for Automated Architectural Reconstruction from Photographs
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ACM SIGGRAPH 2003 Papers
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Detailed Real-Time Urban 3D Reconstruction from Video
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Sketching reality: Realistic interpretation of architectural designs
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MM '11 Proceedings of the 19th ACM international conference on Multimedia
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Reconstructing and exploring massive detailed cityscapes
VAST'11 Proceedings of the 12th International conference on Virtual Reality, Archaeology and Cultural Heritage
O-snap: Optimization-based snapping for modeling architecture
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International Journal of Computer Vision
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ACM Transactions on Graphics (TOG)
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ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
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ACM Transactions on Graphics (TOG)
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ACM Transactions on Graphics (TOG)
Efficient 3D reconstruction for urban scenes
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories
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We introduce an interactive tool which enables a user to quickly assemble an architectural model directly over a 3D point cloud acquired from large-scale scanning of an urban scene. The user loosely defines and manipulates simple building blocks, which we call SmartBoxes, over the point samples. These boxes quickly snap to their proper locations to conform to common architectural structures. The key idea is that the building blocks are smart in the sense that their locations and sizes are automatically adjusted on-the-fly to fit well to the point data, while at the same time respecting contextual relations with nearby similar blocks. SmartBoxes are assembled through a discrete optimization to balance between two snapping forces defined respectively by a data-fitting term and a contextual term, which together assist the user in reconstructing the architectural model from a sparse and noisy point cloud. We show that a combination of the user's interactive guidance and high-level knowledge about the semantics of the underlying model, together with the snapping forces, allows the reconstruction of structures which are partially or even completely missing from the input.