Geometric Refinement of ALS-Data Derived Building Models Using Monoscopic Aerial Images

Airborne laser scanning (ALS) has proven to be a strong basis for 3D building reconstruction. While ALS data allows for a highly automated processing workflow, a major drawback is often in the point spacing. As a consequence, the precision of roof plane and ridge line parameters is usually significantly better than the precision of gutter lines. To cope with this problem, the paper presents an approach for geometric refinement of building models reconstructed from ALS data using monoscopic aerial images. The core idea of the proposed modeling method is to obtain refined roof edges by intersecting roof planes accurately and reliably extracted from 3D point clouds with viewing planes assigned with building edges detected in a high resolution aerial image. In order to minimize ambiguities that may arise during the integration of modeling cues, the ALS data is used as the master providing initial information about building shape and topology. We evaluate the performance of our algorithm by comparing the results of 3D reconstruction executed using only laser scanning data and reconstruction enhanced by image information. The assessment performed within a framework of the International Society for Photogrammetry and Remote Sensing (ISPRS) benchmark shows an increase in the final quality indicator up to 8.7%.

[1]  3D LiDAR BUILDING ROOF REFINEMENT USING PHOTOGRAMMETRIC DATA , 2009 .

[2]  Nusret Demir,et al.  Automated Modeling of 3d Building Roofs Using Image and LIDAR Data , 2012 .

[3]  Tee-Ann Teo,et al.  Building reconstruction from LIDAR data and aerial imagery , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[4]  Jaewook Jung,et al.  Sequential Modelling of Building Rooftops by Integrating Airborne LIDAR Data and Optical Imagery: Preliminary Results , 2013 .

[5]  Norbert Haala,et al.  An update on automatic 3D building reconstruction , 2010 .

[6]  George Vosselman,et al.  Two algorithms for extracting building models from raw laser altimetry data , 1999 .

[7]  Horst Bischof,et al.  Image-based Building Classification and 3D Modelling with Super-Pixels , 2010 .

[8]  Angelina Novachevaa,et al.  BUILDING ROOF RECONSTRUCTION FROM LIDAR DATA AND AERIAL IMAGES THROUGH PLANE EXTRACTION AND COLOUR EDGE DETECTION , 2008 .

[9]  Dimitri Bulatov,et al.  Context-based automatic reconstruction and texturing of 3D urban terrain for quick-response tasks , 2014 .

[10]  Ruijin Ma,et al.  Building model reconstruction from LIDAR data and aerial photographs , 2005 .

[11]  Martin Kada,et al.  3D BUILDING RECONSTRUCTION FROM LIDAR BASED ON A CELL DECOMPOSITION APPROACH , 2009 .

[12]  K. Moffett,et al.  Remote Sens , 2015 .

[13]  Kyoung Mu Lee,et al.  Fusion of Lidar and Imagery for Reliable Building Extraction , 2008 .

[14]  C. Brenner.  Building reconstruction from images and laser scanning , 2005 .

[15]  Markus Gerke,et al.  FITTING OF PARAMETRIC BUILDING MODELS TO OBLIQUE AERIAL IMAGES , 2012 .

[16]  Wen Zhang,et al.  Integration of LiDAR data and optical multi-view images for 3D reconstruction of building roofs , 2013 .

[17]  Wuming Zhang,et al.  3D Building Roof Modeling by Optimizing Primitive's Parameters Using Constraints from LiDAR Data and Aerial Imagery , 2014, Remote. Sens..

[18]  Fabio Remondino,et al.  AUTOMATIC ROOF OUTLINES RECONSTRUCTION FROM PHOTOGRAMMETRIC DSM , 2012 .

[19]  C. Brenner,et al.  A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data , 2013 .

[20]  Frank Ade,et al.  Project Amobe: Strategies, Current Status And Future Work , 1996 .

[21]  M. Jancosek,et al.  Flexible building primitives for 3D building modeling , 2015 .

[22]  Franz Rottensteiner,et al.  AUTOMATIC EXTRACTION OF BUILDINGS FROM LIDAR DATA AND AERIAL IMAGES , 2002 .

[23]  I. Dowman,et al.  Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction * , 2007 .

[24]  Franz Rottensteiner,et al.  ISPRS Test Project on Urban Classification and 3D Building Reconstruction: Evaluation of Building Reconstruction Results , 2009 .

[25]  Mohannad Al-Durgham,et al.  MODEL-BASED AUTOMATIC 3D BUILDING MODEL GENERATION BY INTEGRATING LIDAR AND AERIAL IMAGES , 2011 .

[26]  Claus Brenner,et al.  Generation Of 3D City Models From Airborne Laser Scanning Data , 1997 .

[27]  Michael Cramer,et al.  The DGPF-Test on Digital Airborne Camera Evaluation - Over- view and Test Design , 2010 .

[28]  Jie Shan,et al.  Building roof modeling from airborne laser scanning data based on level set approach , 2011 .

[29]  George Vosselman,et al.  Building Reconstruction by Target Based Graph Matching on Incomplete Laser Data: Analysis and Limitations , 2009, Sensors.

[30]  George Vosselman,et al.  Quality analysis on 3D building models reconstructed from airborne laser scanning data , 2011 .

[31]  Andrzej Borkowski,et al.  3D building reconstruction from ALS data using unambiguous decomposition into elementary structures , 2016 .

[32]  Jaewook Jung,et al.  Results of the ISPRS benchmark on urban object detection and 3D building reconstruction , 2014 .

[33]  Wolfgang Förstner,et al.  Towards automatic building extraction from high-resolution digital elevation models , 1995 .

[34]  Norbert Pfeifer,et al.  A Comparison of Evaluation Techniques for Building Extraction From Airborne Laser Scanning , 2009, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.