Automatic 3D building reconstruction by integration of digital map and stereo imagery for urban area

Yom, Jae-Hong; Lee, Dong-Cheon; Kim, Deok-In

doi:10.1007/bf02829168

Cited by 1 publication

(2 citation statements)

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“…Erroneous image matching due to various problematic situations, such as shadow and occlusion areas by buildings, different reflectance, illumination, and foreshortening from different perspectives, and co-registration errors between image and map coordinates, causes inaccurate estimation of the building height [27], [28]. However, if the height estimations are out of the building height range, or if a height difference is significantly larger compared with heights of the vertices in a building, then those height values are not used in the final building height computation.…”

Section: Image Matchingmentioning

confidence: 99%

“…However, if the height estimations are out of the building height range, or if a height difference is significantly larger compared with heights of the vertices in a building, then those height values are not used in the final building height computation. Erroneous image matching due to various problematic situations, such as shadow and occlusion areas by buildings, different reflectance, illumination, and foreshortening from different perspectives, and co-registration errors between image and map coordinates, causes inaccurate estimation of the building height [27], [28].…”

Section: Image Matchingmentioning

confidence: 99%

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Automatic Building Reconstruction with Satellite Images and Digital Maps

Lee¹,

Yom²,

Shin³

et al. 2011

ETRI J

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This paper introduces an automated method for building height recovery through the integration of high‐resolution satellite images and digital vector maps. A cross‐correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross‐correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

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Section: Image Matchingmentioning

confidence: 99%

Section: Image Matchingmentioning

confidence: 99%