Skip to main content
SpringerLink
Log in
Book cover

Advances in 3D Geoinformation pp 49–62Cite as

Interactive and View-Dependent See-Through Lenses for Massive 3D Point Clouds

  • Chapter
  • First Online:

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

3D point clouds are a digital representation of our world and used in a variety of applications. They are captured with LiDAR or derived by image-matching approaches to get surface information of objects, e.g., indoor scenes, buildings, infrastructures, cities, and landscapes. We present novel interaction and visualization techniques for heterogeneous, time variant, and semantically rich 3D point clouds. Interactive and view-dependent see-through lenses are introduced as exploration tools to enhance recognition of objects, semantics, and temporal changes within 3D point cloud depictions. We also develop filtering and highlighting techniques that are used to dissolve occlusion to give context-specific insights. All techniques can be combined with an out-of-core real-time rendering system for massive 3D point clouds. We have evaluated the presented approach with 3D point clouds from different application domains. The results show the usability and how different visualization and exploration tasks can be improved for a variety of domain-specific applications.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Andújar, C., Vázquez, P., & Fairén, M. (2004). Way-Finder: Guided tours through complex walkthrough models. Computer Graphics Forum, 23(3), 499–508.

    Article  Google Scholar 

  • Brosz, J., Carpendale, S., & Nacenta, M. (2011). The undistort lens. Computer Graphics Forum, 30(3), 881–890.

    Article  Google Scholar 

  • Brosz, J., Samavati, F., Carpendale, S., & Sousa, M. (2007). Single camera flexible projection. In Proceedings of the 5th international symposium on Non-photorealistic animation and rendering (pp. 33–42).

    Google Scholar 

  • Burtnyk, N., Khan, A., Fitzmaurice, G., Balakrishnan, R., & Kurtenbach, G. (2002). StyleCam: Interactive stylized 3D navigation using integrated spatial and temporal controls. In Proceedings of the 15th annual ACM symposium on User interface software and technology (pp. 101–110).

    Google Scholar 

  • Canli, E., Thiebes, B., Höfle, B., & Glade, T. (2015). Permanent 3D laser scanning system for alpine hillslope instabilities. In 6th international conference on debris-flow hazards mitigation: Mechanics, prediction and assessment (pp. 1–1).

    Google Scholar 

  • Elmqvist, N., & Tsigas, P. (2008). A Taxonomy of 3D occlusion management for visualization. IEEE Transactions on Visualization and Computer Graphics, 14(5), 1095–1109.

    Article  Google Scholar 

  • Gao, Z., Nocera, L., Wang, M., & Neumann, U. (2014). Visualizing aerial LiDAR cities with hierarchical hybrid point-polygon structures. In Proceedings of the 2014 graphics interface conference (pp. 137–144).

    Google Scholar 

  • Goesele, M. et al. (2010). Ambient point clouds for view interpolation. ACM Transactions on Graphics, 29(4), 95:1–95:6.

    Google Scholar 

  • Goswami, P., Erol, F., Mukhi, R., Pajarola, R., & Gobbetti, E. (2013). An efficient multiresolution framework for high quality interactive rendering of massive point clouds using multi-way kd-trees. The Visual Computer, 29(1), 69–83.

    Article  Google Scholar 

  • Gross, M., & Pfister, H. (2007). Point-based graphics. Morgan Kaufmann Publishers Inc.

    Google Scholar 

  • Hasan, M., Samavati, F., & Jacob, C. (2014). Multilevel focus + context visualization using balanced multiresolution. In 2014 international conference on cyberworlds (pp. 145–152).

    Google Scholar 

  • Koenig, K. et al. (2015). Comparative classification analysis of post-harvest growth detection from terrestrial LiDAR point clouds in precision agriculture. ISPRS Journal of Photogrammetry and Remote Sensing, 104(0), 112–125.

    Google Scholar 

  • Lafarge, F., & Mallet, C. (2012). Creating large-scale city models from 3d-point clouds: A robust approach with hybrid representation. International Journal of Computer Vision, 99(1), 69–85.

    Article  Google Scholar 

  • Leberl, F. et al. (2010). Point clouds: Lidar versus 3D vision. Photogrammetric Engineering and Remote Sensing, 76(10), 1123–1134

    Google Scholar 

  • Mitra, N., & Nguyen, A. (2003). Estimating surface normals in noisy point cloud data. In 19th annual symposium on computational geometry (pp. 322–328).

    Google Scholar 

  • Nebiker, S., Bleisch, S., & Christen, M. (2010). Rich point clouds in virtual globes—A new paradigm in city modeling? Computers, Environment and Urban Systems, 34(6), 508–517.

    Article  Google Scholar 

  • Nienhaus, M., & Döllner, J. (2004). Blueprint Rendering and ‘Sketchy Drawings’. GPU Gems, II, 235–252.

    Google Scholar 

  • Pasewaldt, S., Semmo, A., Trapp, M., & Döllner, J. (2014). Multi-perspective 3D panoramas. International Journal of Geographical Information Science, 28(10), 2030–2051.

    Article  Google Scholar 

  • Preiner, R., Jeschke, S., & Wimmer, M. (2012). Auto splats: Dynamic point cloud visualization on the GPU. In Proceedings of eurographics symposium on parallel graphics and visualization (pp. 139–148).

    Google Scholar 

  • Richter, R., Behrens, M., & Döllner, J. (2013). Object class segmentation of massive 3D point clouds of urban areas using point cloud topology. International Journal of Remote Sensing, 34(23), 8408–8424.

    Article  Google Scholar 

  • Richter, R., & Döllner, J. (2014). Concepts and techniques for integration, analysis and visualization of massive 3D point clouds. Computers, Environment and Urban Systems, 45, 114–124.

    Article  Google Scholar 

  • Richter, R., Discher, S., & Döllner, J. (2015). Out-of-core visualization of classified 3D point clouds. In 3d geoinformation science: The selected papers of the 3D geoinfo 2014 (pp. 227–242).

    Google Scholar 

  • Ropinski, T., Hinrichs, K., & Steinicke, F. (2005). A solution for the focus and context problem in geo-virtual environments. In Proceedings of the 4th ISPRS workshop on dynamic and multi-dimensional GIS (pp. 144–149).

    Google Scholar 

  • Saito, T., & Takahashi, T. (1990). Comprehensible Rendering of 3-D Shapes. SIGGRAPH Computer Graphics, 24(4), 197–206.

    Article  Google Scholar 

  • Sigg, S., Fuchs, R., Carnecky, R., & Peikert, R. (2012). Intelligent cutaway illustrations. IEEE Pacific Visualization Symposium, 2012, 185–192.

    Google Scholar 

  • Sonnet, H., Carpendale, S., & Strothotte, T. (2004). Integrating expanding annotations with a 3D explosion probe. In Proceedings of the working conference on advanced visual interfaces (pp. 63–70).

    Google Scholar 

  • Tomljenovic, I., Höfle, B., Tiede, D., & Blaschke, T. (2015). Building extraction from airborne laser scanning data: An analysis of the state of the art. Remote Sensing, 7(4), 3826–3862.

    Article  Google Scholar 

  • Trapp, M., Glander, T., Buchholz, H., & Döllner, J. (2008). 3D generalization lenses for interactive focus + context visualization of virtual city models. In 12th international conference on information visualisation (pp. 356–361).

    Google Scholar 

  • Vaaraniemi, M., Freidank, M., & Westermann, R. (2013). Enhancing the visibility of labels in 3D navigation maps. In Progress and new trends in 3D geoinformation sciences (pp. 23–40).

    Google Scholar 

  • Wang, L., Zhao, Y., Mueller, K., & Kaufman, A. (2005). The magic volume lens: An interactive focus + context technique for volume rendering. IEEE Visualization, 2005, 367–374.

    Google Scholar 

  • Xu, H., Nguyen, M., Yuan, X., & Chen, B. (2004). Interactive silhouette rendering for point-based models. In Eurographics symposium on point-based graphics (pp. 13–18).

    Google Scholar 

  • Yu, J., & Turk, G. (2013). Reconstructing surfaces of particle-based fluids using anisotropic kernels. ACM Transactions on Graphics, 32(1), 5:1–5:12.

    Google Scholar 

Download references

Acknowledgments

This work was funded by the Federal Ministry of Education and Research (BMBF), Germany within the InnoProfile Transfer research group “4DnD-Vis” (www.4dndvis.de) and the Research School on ‘Service-Oriented Systems Engineering’ of the Hasso Plattner Institute. We would like to thank virtualcitySYSTEMS and the Faculty of Architecture at the Cologne University of Applied Sciences for providing datasets.

Author information

Authors and Affiliations

  1. Hasso Plattner Institute, University of Potsdam, Potsdam, Germany

    Sören Discher, Rico Richter & Jürgen Döllner

Authors
  1. Sören Discher
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rico Richter
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jürgen Döllner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sören Discher .

Editor information

Editors and Affiliations

  1. Department of Geoinformation, Universiti Teknologi Malaysia, Johor Bahru, Malaysia

    Alias Abdul-Rahman

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Discher, S., Richter, R., Döllner, J. (2017). Interactive and View-Dependent See-Through Lenses for Massive 3D Point Clouds. In: Abdul-Rahman, A. (eds) Advances in 3D Geoinformation. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-25691-7_3

Download citation

Publish with us

Policies and ethics

Search

Navigation