ACM SIGGRAPH Asia 2008 papers
Multi-view Superpixel Stereo in Urban Environments
International Journal of Computer Vision
SmartBoxes for interactive urban reconstruction
ACM SIGGRAPH 2010 papers
Variational model-based 3D building extraction from remote sensing data
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
IEEE Transactions on Image Processing
3D reconstruction using an n-layer heightmap
Proceedings of the 32nd DAGM conference on Pattern recognition
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
Communications of the ACM
Semantic classification in aerial imagery by integrating appearance and height information
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Image-based rendering for scenes with reflections
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Applications of Geometry Processing: Grammar-based 3D facade segmentation and reconstruction
Computers and Graphics
Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
International Journal of Computer Vision
Modeling residential urban areas from dense aerial LiDAR point clouds
CVM'12 Proceedings of the First international conference on Computational Visual Media
Large-scale Structure-from-Motion Reconstruction with small memory consumption
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
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Accurate and realistic building models of urban environments are increasingly important for applications, like virtual tourism or city planning. Initiatives like Virtual Earth or Google Earth are aiming at offering virtual models of all major cities world wide. The prohibitively high costs of manual generation of such models explain the need for an automatic workflow.This paper proposes an algorithm for fully automatic building reconstruction from aerial images. Sparse line features delineating height discontinuities and dense depth data providing the roof surface are combined in an innovative manner with a global optimization algorithm based on Graph Cuts. The fusion process exploits the advantages of both information sources and thus yields superior reconstruction results compared to the indiviual sources. The nature of the algorithm also allows to elegantly generate image driven levels of detail of the geometry.The algorithm is applied to a number of real world data sets encompassing thousands of buildings. The results are analyzed in detail and extensively evaluated using ground truth data.