Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 185-190 |
| Seitenumfang | 6 |
| Fachzeitschrift | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Jahrgang | 1 |
| Publikationsstatus | Veröffentlicht - 20 Juli 2012 |
| Veranstaltung | 22nd Congress of the International Society for Photogrammetry and Remote Sensing: Imaging a Sustainable Future, ISPRS 2012 - Melbourne, Australien Dauer: 25 Aug. 2012 → 1 Sept. 2012 |
Abstract
Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as input a high-quality Digital Surface Model (DSM), are more straight-forward and produce more robust and reliable results than those image-based methods that require matching line segments or even whole regions. This motivated us to develop a new dense matching technique for DSM generation that is capable of simultaneous integration of multiple images in the reconstruction process. The DSMs generated by this new multi-image matching technique can be used for urban object extraction. In the first contribution of this paper, two examples of external sources of information added to the reconstruction pipeline will be shown. The GIS layers are used for recognition of streets and suppressing false alarms in the depth maps that were caused by moving vehicles while the near infrared channel is applied for separating vegetation from buildings. Three examples of data sets including both UAV-borne video sequences with a relatively high number of frames and high-resolution (10 cm ground sample distance) data sets consisting of (few spatial-temporarily diverse) images from large-format aerial frame cameras, will be presented. By an extensive quantitative evaluation of the Vaihingen block from the ISPRS benchmark on urban object detection, it will become clear that our procedure allows a straight-forward, efficient, and reliable instantiation of 3D city models.
ASJC Scopus Sachgebiete
- Erdkunde und Planetologie (insg.)
- Erdkunde und Planetologie (sonstige)
- Umweltwissenschaften (insg.)
- Umweltwissenschaften (sonstige)
- Physik und Astronomie (insg.)
- Instrumentierung
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in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Jahrgang 1, 20.07.2012, S. 185-190.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - CONTEXT-BASED URBAN TERRAIN RECONSTRUCTION from IMAGES and VIDEOS
AU - Bulatov, D.
AU - Rottensteiner, F.
AU - Schulz, K.
PY - 2012/7/20
Y1 - 2012/7/20
N2 - Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as input a high-quality Digital Surface Model (DSM), are more straight-forward and produce more robust and reliable results than those image-based methods that require matching line segments or even whole regions. This motivated us to develop a new dense matching technique for DSM generation that is capable of simultaneous integration of multiple images in the reconstruction process. The DSMs generated by this new multi-image matching technique can be used for urban object extraction. In the first contribution of this paper, two examples of external sources of information added to the reconstruction pipeline will be shown. The GIS layers are used for recognition of streets and suppressing false alarms in the depth maps that were caused by moving vehicles while the near infrared channel is applied for separating vegetation from buildings. Three examples of data sets including both UAV-borne video sequences with a relatively high number of frames and high-resolution (10 cm ground sample distance) data sets consisting of (few spatial-temporarily diverse) images from large-format aerial frame cameras, will be presented. By an extensive quantitative evaluation of the Vaihingen block from the ISPRS benchmark on urban object detection, it will become clear that our procedure allows a straight-forward, efficient, and reliable instantiation of 3D city models.
AB - Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as input a high-quality Digital Surface Model (DSM), are more straight-forward and produce more robust and reliable results than those image-based methods that require matching line segments or even whole regions. This motivated us to develop a new dense matching technique for DSM generation that is capable of simultaneous integration of multiple images in the reconstruction process. The DSMs generated by this new multi-image matching technique can be used for urban object extraction. In the first contribution of this paper, two examples of external sources of information added to the reconstruction pipeline will be shown. The GIS layers are used for recognition of streets and suppressing false alarms in the depth maps that were caused by moving vehicles while the near infrared channel is applied for separating vegetation from buildings. Three examples of data sets including both UAV-borne video sequences with a relatively high number of frames and high-resolution (10 cm ground sample distance) data sets consisting of (few spatial-temporarily diverse) images from large-format aerial frame cameras, will be presented. By an extensive quantitative evaluation of the Vaihingen block from the ISPRS benchmark on urban object detection, it will become clear that our procedure allows a straight-forward, efficient, and reliable instantiation of 3D city models.
KW - Building Reconstruction
KW - Depth Map
KW - Digital Surface Model
KW - Free Geographic Data
KW - Near Infrared
KW - Vegetation
UR - http://www.scopus.com/inward/record.url?scp=85010667262&partnerID=8YFLogxK
U2 - 10.5194/isprsannals-I-3-185-2012
DO - 10.5194/isprsannals-I-3-185-2012
M3 - Conference article
AN - SCOPUS:85010667262
VL - 1
SP - 185
EP - 190
JO - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
SN - 2194-9042
T2 - 22nd Congress of the International Society for Photogrammetry and Remote Sensing: Imaging a Sustainable Future, ISPRS 2012
Y2 - 25 August 2012 through 1 September 2012
ER -