A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting buildings in aerial images
Computer Vision, Graphics, and Image Processing
Automating knowledge acquisition for aerial image interpretation
Computer Vision, Graphics, and Image Processing
Using Perceptual Organization to Extract 3D Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of shadows for extracting buildings in aerial images
Computer Vision, Graphics, and Image Processing
An optimization framework for feature extraction
Machine Vision and Applications
Fusion of monocular cues to detect man-made structures in aerial imagery
CVGIP: Image Understanding
3-D reconstruction of urban scenes from image sequences
Computer Vision and Image Understanding - Special issue on CAD-based computer vision
The ascender system: automated site modeling from multiple aerial images
Computer Vision and Image Understanding
The role of color attributes and similarity grouping in 3-D building reconstruction
Computer Vision and Image Understanding
Extracting buildings from aerial images using hierachical aggregation in 2D and 3D
Computer Vision and Image Understanding
Spherical Mosaics with Quaternions and Dense Correlation
International Journal of Computer Vision
Detection and Modeling of Buildings from Multiple Aerial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accurate building structure recovery from high resolution aerial imagery
Computer Vision and Image Understanding
Robot Vision
Retrieving Shape Information from Multiple Images of a Specular Surface
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Spherical Representation for Recognition of Free-Form Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Modeling and 3D Reconstruction of Urban House Roofs from High Resolution Aerial Imagery
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Building Reconstruction from Optical and Range Images
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Automatic model acquisition and aerial image understanding
Automatic model acquisition and aerial image understanding
Automated construction activity monitoring system
Advanced Engineering Informatics
A Polygon Detection Algorithm for Robot Visual Servoing
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Generation of 3D City Models Using Domain-Specific Information Fusion
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
Rooftop Detection and 3D Building Modeling from Aerial Images
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
An Automation System of Rooftop Detection and 3D Building Modeling from Aerial Images
Journal of Intelligent and Robotic Systems
Inferring and enforcing geometrical constraints on a 3d model for building reconstruction
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Archaeological trace extraction by a local directional active contour approach
Pattern Recognition
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We present a model-based approach to the automatic detection and reconstruction of buildings from aerial imagery. Buildings are first segmented from the scene in an optical image followed by a reconstruction process that makes use of a corresponding digital elevation map (DEM). Initially, each segmented DEM region likely to contain a building rooftop is indexed into a database of parameterized surface models that represent different building shape classes such as peaked, flat, or curved roofs. Given a set of indexed models, each is fit to the elevation data using a robust iterative procedure that determines the precise position and shape of the building rooftop. The indexed model that converges to the data with the lowest residual fit error is then added to the scene by extruding the fit rooftop surfaces to a local ground plane.The approach is based on the observation that a significant amount of rooftop variation can be modeled as the union of a small set of parameterized models and their combinations. By first recognizing the rooftop as one of the several potential rooftop shapes and fitting only these surfaces, the technique remains robust while still capable of reconstructing a wide variety of building types. In contrast to earlier approaches that presuppose a particular class of rooftops to be reconstructed (e.g., flat roofs), the algorithm is capable of reconstructing a variety of building types including peaked, flat, multi-level flat, and curved surfaces. The approach is evaluated on two datasets. Recognition rates for the different building rooftop classes and reconstruction accuracy are reported.