Urban building detection from optical and insar features exploiting context

J. D. Wegner; A. O. Ok; A. Thiele; F. Rottensteiner; U. Soergel

Urban building detection from optical and insar features exploiting context

J. D. Wegner
, A. O. Ok
, A. Thiele
, F. Rottensteiner
, U. Soergel

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

We investigate the potential of combined features of aerial images and high-resolution interferometric SAR (InSAR) data for building detection in urban areas. It is shown that completeness and correctness may be increased if we integrate both InSAR double-bounce lines and 3D lines of stereo data in addition to building hints of a single optical orthophoto. In order to exploit context information, which is crucial for object detection in urban areas, we use a Conditional Random Field approach. It proves to be a valuable method for context-based building detection with multi-sensor features.

Original language	English
Pages (from-to)	239-244
Number of pages	6
Journal	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume	38
Publication status	Published - 2010
Externally published	Yes
Event	ISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis, PCV 2010 - Saint-Mande, France Duration: 1 Sept 2010 → 3 Sept 2010

Keywords

Conditional Random Fields
Fusion
InSAR Data
Optical Stereo Data
Remote Sensing
Urban Area

Cite this

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title = "Urban building detection from optical and insar features exploiting context",

abstract = "We investigate the potential of combined features of aerial images and high-resolution interferometric SAR (InSAR) data for building detection in urban areas. It is shown that completeness and correctness may be increased if we integrate both InSAR double-bounce lines and 3D lines of stereo data in addition to building hints of a single optical orthophoto. In order to exploit context information, which is crucial for object detection in urban areas, we use a Conditional Random Field approach. It proves to be a valuable method for context-based building detection with multi-sensor features.",

keywords = "Conditional Random Fields, Fusion, InSAR Data, Optical Stereo Data, Remote Sensing, Urban Area",

author = "Wegner, \{J. D.\} and Ok, \{A. O.\} and A. Thiele and F. Rottensteiner and U. Soergel",

year = "2010",

language = "English",

volume = "38",

pages = "239--244",

journal = "International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives",

issn = "1682-1750",

publisher = "International Society for Photogrammetry and Remote Sensing",

note = "ISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis, PCV 2010 ; Conference date: 01-09-2010 Through 03-09-2010",

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TY - JOUR

T1 - Urban building detection from optical and insar features exploiting context

AU - Wegner, J. D.

AU - Ok, A. O.

AU - Thiele, A.

AU - Rottensteiner, F.

AU - Soergel, U.

PY - 2010

Y1 - 2010

N2 - We investigate the potential of combined features of aerial images and high-resolution interferometric SAR (InSAR) data for building detection in urban areas. It is shown that completeness and correctness may be increased if we integrate both InSAR double-bounce lines and 3D lines of stereo data in addition to building hints of a single optical orthophoto. In order to exploit context information, which is crucial for object detection in urban areas, we use a Conditional Random Field approach. It proves to be a valuable method for context-based building detection with multi-sensor features.

AB - We investigate the potential of combined features of aerial images and high-resolution interferometric SAR (InSAR) data for building detection in urban areas. It is shown that completeness and correctness may be increased if we integrate both InSAR double-bounce lines and 3D lines of stereo data in addition to building hints of a single optical orthophoto. In order to exploit context information, which is crucial for object detection in urban areas, we use a Conditional Random Field approach. It proves to be a valuable method for context-based building detection with multi-sensor features.

KW - Conditional Random Fields

KW - Fusion

KW - InSAR Data

KW - Optical Stereo Data

KW - Remote Sensing

KW - Urban Area

UR - https://www.scopus.com/pages/publications/84923870536

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M3 - Conference article

AN - SCOPUS:84923870536

SN - 1682-1750

VL - 38

SP - 239

EP - 244

JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

T2 - ISPRS Technical Commission III Symposium on Photogrammetric Computer Vision and Image Analysis, PCV 2010

Y2 - 1 September 2010 through 3 September 2010

ER -

Urban building detection from optical and insar features exploiting context

Abstract

Keywords

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