Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 329-334 |
| Seitenumfang | 6 |
| Fachzeitschrift | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Jahrgang | 1 |
| Publikationsstatus | Veröffentlicht - 23 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
This paper describes a semi-automatic system for road verification based on high resolution imagery and 3D surface models. Potential update regions are identified by an object-wise verification of all existing database records. The proposed system combines several road detection and road verification approaches from current literature to form a more general solution. Each road detection / verification approach is realized as an independent module representing a unique road model combined with a corresponding processing strategy. The object-wise verification result of each module is formulated as a binary decision between the classes "correct road" and "incorrect road". These individual decisions are combined by Dempster-Shafer fusion, which provides tools for dealing with uncertain and incomplete knowledge about the statistical properties of the data. For each road detection / verification module a confidence function for the result is introduced that reflects the degree of correspondence of an actual test situation with an optimal situation according to the underlying road model of that module. A comparison with results from an EuroSDR test on road extraction demonstrate the strengths and limitations of the method.
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, 23.07.2012, S. 329-334.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - MULTIPLE-MODEL BASED VERIFICATION of ROAD DATA
AU - Ziems, M.
AU - Breitkopf, U.
AU - Heipke, C.
AU - Rottensteiner, F.
PY - 2012/7/23
Y1 - 2012/7/23
N2 - This paper describes a semi-automatic system for road verification based on high resolution imagery and 3D surface models. Potential update regions are identified by an object-wise verification of all existing database records. The proposed system combines several road detection and road verification approaches from current literature to form a more general solution. Each road detection / verification approach is realized as an independent module representing a unique road model combined with a corresponding processing strategy. The object-wise verification result of each module is formulated as a binary decision between the classes "correct road" and "incorrect road". These individual decisions are combined by Dempster-Shafer fusion, which provides tools for dealing with uncertain and incomplete knowledge about the statistical properties of the data. For each road detection / verification module a confidence function for the result is introduced that reflects the degree of correspondence of an actual test situation with an optimal situation according to the underlying road model of that module. A comparison with results from an EuroSDR test on road extraction demonstrate the strengths and limitations of the method.
AB - This paper describes a semi-automatic system for road verification based on high resolution imagery and 3D surface models. Potential update regions are identified by an object-wise verification of all existing database records. The proposed system combines several road detection and road verification approaches from current literature to form a more general solution. Each road detection / verification approach is realized as an independent module representing a unique road model combined with a corresponding processing strategy. The object-wise verification result of each module is formulated as a binary decision between the classes "correct road" and "incorrect road". These individual decisions are combined by Dempster-Shafer fusion, which provides tools for dealing with uncertain and incomplete knowledge about the statistical properties of the data. For each road detection / verification module a confidence function for the result is introduced that reflects the degree of correspondence of an actual test situation with an optimal situation according to the underlying road model of that module. A comparison with results from an EuroSDR test on road extraction demonstrate the strengths and limitations of the method.
KW - Aerial
KW - Classification
KW - Model
KW - Quality
KW - Road database
KW - Updating
UR - http://www.scopus.com/inward/record.url?scp=85027091477&partnerID=8YFLogxK
U2 - 10.5194/isprsannals-I-3-329-2012
DO - 10.5194/isprsannals-I-3-329-2012
M3 - Conference article
AN - SCOPUS:85027091477
VL - 1
SP - 329
EP - 334
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 -