TY - JOUR

T1 - CONDITIONAL RANDOM FIELDS for LIDAR POINT CLOUD CLASSIFICATION in COMPLEX URBAN AREAS

AU - Niemeyer, J.

AU - Rottensteiner, F.

AU - Soergel, U.

PY - 2012/7/13

Y1 - 2012/7/13

N2 - In this paper, we investigate the potential of a Conditional Random Field (CRF) approach for the classification of an airborne LiDAR (Light Detection And Ranging) point cloud. This method enables the incorporation of contextual information and learning of specific relations of object classes within a training step. Thus, it is a powerful approach for obtaining reliable results even in complex urban scenes. Geometrical features as well as an intensity value are used to distinguish the five object classes building, low vegetation, tree, natural ground, and asphalt ground. The performance of our method is evaluated on the dataset of Vaihingen, Germany, in the context of the 'ISPRS Test Project on Urban Classification and 3D Building Reconstruction'. Therefore, the results of the 3D classification were submitted as a 2D binary label image for a subset of two classes, namely building and tree.

AB - In this paper, we investigate the potential of a Conditional Random Field (CRF) approach for the classification of an airborne LiDAR (Light Detection And Ranging) point cloud. This method enables the incorporation of contextual information and learning of specific relations of object classes within a training step. Thus, it is a powerful approach for obtaining reliable results even in complex urban scenes. Geometrical features as well as an intensity value are used to distinguish the five object classes building, low vegetation, tree, natural ground, and asphalt ground. The performance of our method is evaluated on the dataset of Vaihingen, Germany, in the context of the 'ISPRS Test Project on Urban Classification and 3D Building Reconstruction'. Therefore, the results of the 3D classification were submitted as a 2D binary label image for a subset of two classes, namely building and tree.

KW - Classification

KW - Conditional Random Fields

KW - LiDAR

KW - Point Cloud

KW - Urban

UR - http://www.scopus.com/inward/record.url?scp=85041430565&partnerID=8YFLogxK

U2 - 10.5194/isprsannals-I-3-263-2012

DO - 10.5194/isprsannals-I-3-263-2012

M3 - Conference article

AN - SCOPUS:85041430565

VL - 1

SP - 263

EP - 268

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 -