Incremental reconstruction of 3D scenes from multiple, complex images
Artificial Intelligence
Detecting buildings in aerial images
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
Building Reconstruction from Optical and Range Images
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
SiteCity: A Semi-Automated Site Modelling System
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Projective geometry and photometry for object detection and delineation
Projective geometry and photometry for object detection and delineation
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
View Alignment of Aerial and Terrestrial Imagery in Urban Environments
ISD '99 Selected Papers from the International Workshop on Integrated Spatial Databases, Digital Inages and GIS
State of the art on automatic road extraction for GIS update: a novel classification
Pattern Recognition Letters
A system to detect houses and residential street networks in multispectral satellite images
Computer Vision and Image Understanding
Hierarchical shadow detection for color aerial images
Computer Vision and Image Understanding
EURASIP Journal on Applied Signal Processing
Rapid damage assessment of built-up structures using VHR satellite data in tsunami-affected areas
International Journal of Remote Sensing - Satellite Observations Related to Sumatra Tsunami and Earthquake of 26 December 2004
Performance Modeling and Algorithm Characterization for Robust Image Segmentation
International Journal of Computer Vision
Validation of vector data using oblique images
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Discovery of feature-based hot spots using supervised clustering
Computers & Geosciences
Hierarchical shadow detection for color aerial images
Computer Vision and Image Understanding
A system to detect houses and residential street networks in multispectral satellite images
Computer Vision and Image Understanding
An improved snake model for building detection from urban aerial images
Pattern Recognition Letters
A cooperative framework for segmentation of MRI brain scans
Artificial Intelligence in Medicine
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Research in monocular building extraction from aerial imagery has neglected performance evaluation in three areas: unbiased metrics for quantifying detection and delineation performance, an evaluation methodology for applying these metrics to a representative body of test imagery, and an approach for understanding the impact of image and scene content on building extraction algorithms. This paper addresses these areas with an end-to-end performance evaluation of four existing monocular building extraction systems, using image space and object space-based metrics on 83 test images of 18 sites. This analysis is supplemented by an examination of the effects of image obliquity and object complexity on system performance, as well as a case study on the effects of edge fragmentation. This widely applicable performance evaluation approach highlights the consequences of various traditional assumptions about camera geometry, image content, and scene structure, and demonstrates the utility of rigorous photogrammetric object space modeling and primitive-based representations for building extraction.