Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
New Techniques for Automated Architectural Reconstruction from Photographs
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Geometric Grouping of Repeated Elements within Images
Shape, Contour and Grouping in Computer Vision
Constructing 3D City Models by Merging Aerial and Ground Views
IEEE Computer Graphics and Applications
Monitoring Usage of Workstations with a Relational Database
LISA '94 Proceedings of the 8th USENIX conference on System administration
Procedural modeling of buildings
ACM SIGGRAPH 2006 Papers
Towards Urban 3D Reconstruction from Video
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Discovering structural regularity in 3D geometry
ACM SIGGRAPH 2008 papers
Interactive 3D architectural modeling from unordered photo collections
ACM SIGGRAPH Asia 2008 papers
ACM SIGGRAPH Asia 2008 papers
Content-preserving warps for 3D video stabilization
ACM SIGGRAPH 2009 papers
Automatic Creation of Massive Virtual Cities
VR '09 Proceedings of the 2009 IEEE Virtual Reality Conference
Photorealistic Large-Scale Urban City Model Reconstruction
IEEE Transactions on Visualization and Computer Graphics
Image-based street-side city modeling
ACM SIGGRAPH Asia 2009 papers
Structural Approach for Building Reconstruction from a Single DSM
IEEE Transactions on Pattern Analysis and Machine Intelligence
SmartBoxes for interactive urban reconstruction
ACM SIGGRAPH 2010 papers
Detecting large repetitive structures with salient boundaries
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Building Rome on a cloudless day
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Semantic segmentation of urban scenes using dense depth maps
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
2.5D dual contouring: a robust approach to creating building models from Aerial LiDAR point clouds
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
GlobFit: consistently fitting primitives by discovering global relations
ACM SIGGRAPH 2011 papers
Large-scale, dense city reconstruction from user-contributed photos
Computer Vision and Image Understanding
2.5D building modeling by discovering global regularities
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
2D-3D fusion for layer decomposition of urban facades
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Building large urban environments from unstructured point data
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Automatic Extraction of Manhattan-World Building Masses from 3D Laser Range Scans
IEEE Transactions on Visualization and Computer Graphics
An interactive approach to semantic modeling of indoor scenes with an RGBD camera
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Reconstructing the world's museums
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
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We present a complete system to semantically decompose and reconstruct 3D models from point clouds. Different than previous urban modeling approaches, our system is designed for residential scenes, which consist of mainly low-rise buildings that do not exhibit the regularity and repetitiveness as high-rise buildings in downtown areas. Our system first automatically labels the input into distinctive categories using supervised learning techniques. Based on the semantic labels, objects in different categories are reconstructed with domain-specific knowledge. In particular, we present a novel building modeling scheme that aims to decompose and fit the building point cloud into basic blocks that are block-wise symmetric and convex. This building representation and its reconstruction algorithm are flexible, efficient, and robust to missing data. We demonstrate the effectiveness of our system on various datasets and compare our building modeling scheme with other state-of-the-art reconstruction algorithms to show its advantage in terms of both quality and speed.