Quantitative evaluation strategies for urban 3D model generation from remote sensing data

Over the last decade, several automatic approaches have been proposed to reconstruct 3D building models from aerial laser scanning (ALS) data. Typically, they have been benchmarked with data sets having densities of less than 25 points/m2. However, these test data sets lack significant geometric points on vertical surfaces. With recent sensor improvements in airborne laser scanners and changes in flight path planning, the quality and density of ALS data have improved significantly. The paper presents quantitative evaluation strategies for building extraction and reconstruction when using dense data sets. The evaluation strategies measure not only the capacity of a method to detect and reconstruct individual buildings but also the quality of the reconstructed building models in terms of shape similarity and positional accuracy. The paper presents the evaluation strategies for 3D building detection and building model reconstruction based on dense ALS data to benchmark the results in terms of quantifying the quality of the models, with respect to geometrical accuracy and the desired level of detail.Display Omitted High density aerial laser scanning data, approximate 225 points/m2.Building detection and building reconstruction from point clouds of urban building.Evaluation strategies for 3D building detection and building model reconstruction.Evaluation examining identical location, shape similarity and positional accuracy.Proposed method for generating building outlines.

[1]  Andrew M. Day,et al.  Automatically generating large urban environments based on the footprint data of buildings , 2003, SM '03.

[2]  George Vosselman,et al.  EXTRACTING WINDOWS FROM TERRESTRIAL LASER SCANNING , 2007 .

[3]  George Vosselman,et al.  Accuracy of 3D city models: EuroSDR comparison , 2005 .

[4]  Jürgen Döllner,et al.  Object class segmentation of massive 3D point clouds of urban areas using point cloud topology , 2013 .

[5]  Debra F. Laefer,et al.  Validating Computational Models from Laser Scanning Data for Historic Facades , 2013 .

[6]  Hans-Gerd Maas,et al.  Automatic Building Facade Detection in Mobile Laser Scanner point Clouds , 2012 .

[7]  Jinfei Wang,et al.  An Evaluation System for Building Footprint Extraction From Remotely Sensed Data , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

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

[9]  Jefferey A. Shufelt,et al.  Performance Evaluation and Analysis of Monocular Building Extraction From Aerial Imagery , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Debra F. Laefer,et al.  Combining an Angle Criterion with Voxelization and the Flying Voxel Method in Reconstructing Building Models from LiDAR Data , 2013, Comput. Aided Civ. Infrastructure Eng..

[11]  Hans-Gerd Maas,et al.  Cycle graph analysis for 3D roof structure modelling: Concepts and performance , 2014 .

[12]  George Vosselman,et al.  Airborne and terrestrial laser scanning , 2011, Int. J. Digit. Earth.

[13]  Gerhard H. Bendels,et al.  Detecting Holes in Point Set Surfaces , 2006 .

[14]  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.

[15]  S. J. Oude Elberink,et al.  A graph edit dictionary for correcting errors in roof topology graphs reconstructed from point clouds , 2014 .

[16]  C. Fraser,et al.  Automatic Building Extraction From LIDAR Data Covering Complex Urban Scenes , 2014 .

[17]  Debra F. Laefer,et al.  Generation of a Building Typology for Risk Assessment due to Urban Tunnelling , 2012 .

[18]  Ulrich Neumann,et al.  2.5D Dual Contouring: A Robust Approach to Creating Building Models from Aerial LiDAR Point Clouds , 2010, ECCV.

[19]  Juha Hyyppä,et al.  ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007. Espoo, Finland, September 12-14, 2007 , 2007 .

[20]  M. Rutzinger,et al.  Extraction of building footprints from airborne laser scanning: Comparison and validation techniques , 2007, 2007 Urban Remote Sensing Joint Event.

[21]  T. Rabbani,et al.  SEGMENTATION OF POINT CLOUDS USING SMOOTHNESS CONSTRAINT , 2006 .

[22]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Debra F. Laefer,et al.  Flight Optimization Algorithms for Aerial LiDAR Capture for Urban Infrastructure Model Generation , 2009 .

[24]  Brian Okorn,et al.  Toward Automated Modeling of Floor Plans , 2010 .

[25]  George Vosselman,et al.  Segmentation of point clouds using smoothness constraints , 2006 .

[26]  Debra F. Laefer,et al.  Generation of a Building Typology for Urban Tunnelling Risk Assessment , 2012 .

[27]  Debra F. Laefer,et al.  Flying Voxel Method with Delaunay Triangulation Criterion for Façade/Feature Detection for Computation , 2012, J. Comput. Civ. Eng..

[28]  Clive S. Fraser,et al.  An Automatic and Threshold-Free Performance Evaluation System for Building Extraction Techniques From Airborne LIDAR Data , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.