ML Anthology

Detection and Description of Buildings from Multiple Aerial Images

Sanjay Noronha, Ramakant Nevatia
CVPR 1997 pp. 588-594
doi:10.1109/CVPR.1997.609385 /cvpr/1997/noronha1997cvpr-detection/

Abstract

A method for detection and description of rectangular buildings from two or more registered aerial intensity images is proposed. The output is a 3D description of the buildings, with an associated confidence measure for each building. Hierarchical perceptual grouping and matching across views is employed to increase the robustness of the system. Verification of selected building hypotheses is done using shadow and wall evidence of the buildings. The system is largely feature-based. Grouping and matching are performed in a hierarchical manner utilizing primitives of increasing complexity, starting with line segments and junctions, and proceeding to higher level features. Binocular and trinocular epipolar constraints are used to reduce the search space for matching features.

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Cite

Text

Noronha and Nevatia. "Detection and Description of Buildings from Multiple Aerial Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997. doi:10.1109/CVPR.1997.609385

Markdown

[Noronha and Nevatia. "Detection and Description of Buildings from Multiple Aerial Images." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1997.](https://mlanthology.org/cvpr/1997/noronha1997cvpr-detection/) doi:10.1109/CVPR.1997.609385

BibTeX

@inproceedings{noronha1997cvpr-detection,
  title     = {{Detection and Description of Buildings from Multiple Aerial Images}},
  author    = {Noronha, Sanjay and Nevatia, Ramakant},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1997},
  pages     = {588-594},
  doi       = {10.1109/CVPR.1997.609385},
  url       = {https://mlanthology.org/cvpr/1997/noronha1997cvpr-detection/}
}