SELF-LOCALIZATION OF A MULTI-FISHEYE CAMERA BASED AUGMENTED REALITY SYSTEM IN TEXTURELESS 3D BUILDING MODELS

Urban, S.; Leitloff, J.; Wursthorn, S.; Hinz, S.

Georeferenced images help planners to compare and document the progress of underground construction sites. As underground positioning can not rely on GPS/GNSS, we introduce a solely vision based localization method, that makes use of a textureless 3D CAD model of the construction site. In our analysis-by-synthesis approach, depth and normal fisheye images are rendered from presampled positions and gradient orientations are extracted to build a high dimensional synthetic feature space. Acquired camera images are then matched to those features by using a robust distance metric and fast nearest neighbor search. In this manner, initial poses can be obtained on a laptop in real-time using concurrent processing and the graphics processing unit.

Zitieren

Zitierform:

Urban, S. / Leitloff, J. / Wursthorn, S. / et al: SELF-LOCALIZATION OF A MULTI-FISHEYE CAMERA BASED AUGMENTED REALITY SYSTEM IN TEXTURELESS 3D BUILDING MODELS. 2013. Copernicus Publications.

Zugriffsstatistik

Gesamt:
Volltextzugriffe:
Metadatenansicht:
12 Monate:
Volltextzugriffe:
Metadatenansicht:

Grafik öffnen

Rechte

Rechteinhaber: S. Urban et al.

Nutzung und Vervielfältigung:

Export