Abstract
We present an automatic system to reconstruct 3D urban models for residential areas from aerial LiDAR scans. The key difference between downtown area modeling and residential area modeling is that the latter usually contains rich vegetation. Thus, we propose a robust classification algorithm that effectively classifies LiDAR points into trees, buildings, and ground. The classification algorithm adopts an energy minimization scheme based on the 2.5D characteristic of building structures: buildings are composed of opaque skyward roof surfaces and vertical walls, making the interior of building structures invisible to laser scans; in contrast, trees do not possess such characteristic and thus point samples can exist underneath tree crowns. Once the point cloud is successfully classified, our system reconstructs buildings and trees respectively, resulting in a hybrid model representing the 3D urban reality of residential areas.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE PAMI (2001) 5
Chen, G., Zakhor, A.: 2d tree detection in large urban landscapes using aerial lidar data. In: IEEE ICIP (2009) 4
Côté, J.F., Widlowski, J.L., Fournier, R.A., Verstraete, M.M.: The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial lidar. Remote Sensing of Environment (2009) 4
Lafarge, F., Descombes, X., Zerubia, J., Pierrot-Deseilligny, M.: Building reconstruction from a single dem. In: CVPR (2008) 2, 3
Lafarge, F., Mallet, C.: Building large urban environments from unstructured point data. In: ICCV (2011) 2, 4, 5
Livny, Y., Pirk, S., Cheng, Z., Yan, F., Deussen, O., Cohen-Or, D., Chen, B.: Texture-lobes for tree modelling. In: ACM SIGGRAPH (2011) 4
Lodha, S.K., Fitzpatrick, D.M., Helmbold, D.P.: Aerial lidar data classification using adaboost. In: 3DIM (2007) 4
Matei, B., Sawhney, H., Samarasekera, S., Kim, J., Kumar, R.: Building segmentation for densely built urban regions using aerial lidar data. In: CVPR (2008) 2, 3, 4
Neubert, B., Franken, T., Deussen, O.: Approximate image-based tree-modeling using particle flows. In: ACM SIGGRAPH (2007) 4
Poullis, C., You, S.: Automatic reconstruction of cities from remote sensor data. In: CVPR (2009) 2, 3, 4
Secord, J., Zakhor, A.: Tree detection in urban regions using aerial lidar and image data. IEEE Geoscience and Remote Sensing Letters (2007) 4
Tan, P., Fang, T., Xiao, J., Zhao, P., Quan, L.: Single image tree modeling. ACM SIGGRAPH Asia (2008) 4
Tan, P., Zeng, G., Wang, J., Kang, S.B., Quan, L.: Image-based tree modeling. In: ACM SIGGRAPH (2007) 4
Toshev, A., Mordohai, P., Taskar, B.: Detecting and parsing architecture at city scale from range data. In: CVPR (2010) 3, 4
Verma, V., Kumar, R., Hsu, S.: 3d building detection and modeling from aerial lidar data. In: CVPR (2006) 2, 3, 4
Xu, H., Gossett, N., Chen, B.: Knowledge and heuristic-based modeling of laser-scanned trees. ACM Trans. Graph. (2007) 4
Zebedin, L., Bauer, J., Karner, K., Bischof, H.: Fusion of Feature- and Area-Based Information for Urban Buildings Modeling from Aerial Imagery. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 873–886. Springer, Heidelberg (2008) 3
Zhou, Q.Y., Neumann, U.: A streaming framework for seamless building reconstruction from large-scale aerial lidar data. In: CVPR (2009) 2, 3, 4
Zhou, Q.-Y., Neumann, U.: 2.5D Dual Contouring: A Robust Approach to Creating Building Models from Aerial LiDAR Point Clouds. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part III. LNCS, vol. 6313, pp. 115–128. Springer, Heidelberg (2010) 2, 4, 6
Zhou, Q.Y., Neumann, U.: 2.5d building modeling with topology control. In: CVPR (2011) 2, 4
Zhou, Q.Y., Neumann, U.: 2.5d building modeling by discovering global regularities. In: CVPR (2012) 2, 4
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhou, QY., Neumann, U. (2012). Modeling Residential Urban Areas from Dense Aerial LiDAR Point Clouds. In: Hu, SM., Martin, R.R. (eds) Computational Visual Media. CVM 2012. Lecture Notes in Computer Science, vol 7633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34263-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-34263-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34262-2
Online ISBN: 978-3-642-34263-9
eBook Packages: Computer ScienceComputer Science (R0)