TY - GEN
T1 - SmartBoxes for interactive urban reconstruction
AU - Nan, Liangliang
AU - Sharf, Andrei
AU - Zhang, Hao
AU - Cohen-Or, Daniel
AU - Chen, Baoquan
N1 - Funding Information:
Acknowledgements We thank the anonymous reviewers for their valuable suggestions. This work was supported in part by National Natural Science Foundation of China (60902104), National High-tech R&D Program of China (2009AA01Z302), CAS Visiting Professorship for Senior International Scientists, CAS Fellowship for Young International Scientists, Shenzhen Science and Technology Foundation (GJ200807210013A), and the Natural Sciences and Engineering Research Council of Canada (No. 611370).
Publisher Copyright:
© 2010 ACM.
PY - 2010/7/26
Y1 - 2010/7/26
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84455191493&partnerID=8YFLogxK
U2 - 10.1145/1778765.1778830
DO - 10.1145/1778765.1778830
M3 - Conference contribution
AN - SCOPUS:84455191493
T3 - ACM SIGGRAPH 2010 Papers, SIGGRAPH 2010
BT - ACM SIGGRAPH 2010 Papers, SIGGRAPH 2010
A2 - Hoppe, Hugues
PB - Association for Computing Machinery, Inc
T2 - 37th International Conference and Exhibition on Computer Graphics and Interactive Techniques, SIGGRAPH 2010
Y2 - 26 July 2010 through 30 July 2010
ER -