Introduction to Algorithms
Learning to Locate an Object in 3D Space from a Sequence of Camera Images
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Monitoring Usage of Workstations with a Relational Database
LISA '94 Proceedings of the 8th USENIX conference on System administration
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
Fast Compact City Modeling for Navigation Pre-Visualization
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Detailed Real-Time Urban 3D Reconstruction from Video
International Journal of Computer Vision
3D Urban Scene Modeling Integrating Recognition and Reconstruction
International Journal of Computer Vision
Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Fusion of Feature- and Area-Based Information for Urban Buildings Modeling from Aerial Imagery
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Image-based street-side city modeling
ACM SIGGRAPH Asia 2009 papers
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Real-time 3D reconstruction at scale using voxel hashing
ACM Transactions on Graphics (TOG)
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We present a novel method for 3D reconstruction of urban scenes extending a recently introduced heightmap model. Our model has several advantages for 3D modeling of urban scenes: it naturally enforces vertical surfaces, has no holes, leads to an efficient algorithm, and is compact in size. We remove the major limitation of the heightmap by enabling modeling of overhanging structures. Our method is based on an an n-layer heightmap with each layer representing a surface between full and empty space. The configuration of layers can be computed optimally using a dynamic programming method. Our cost function is derived from probabilistic occupancy, and incorporates the Bayesian Information Criterion (BIC) for selecting the number of layers to use at each pixel. 3D surface models are extracted from the heightmap. We show results from a variety of datasets including Internet photo collections. Our method runs on the GPU and the complete system processes video at 13 Hz.