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Adding the Third Dimension to a Topographic Database Using Airborne Laser Scanner Data

Adding the Third Dimension to a Topographic Database Using Airborne Laser Scanner Data. Sander Oude Elberink Delft, 1 st September 2006. Contents. Introduction Data properties Laser data Map data Approach Densifying 2d map Segmentation 3D reconstruction process (incl. processing rules)

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Adding the Third Dimension to a Topographic Database Using Airborne Laser Scanner Data

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  1. Adding the Third Dimension to a Topographic Database Using Airborne Laser Scanner Data Sander Oude Elberink Delft, 1st September 2006

  2. Contents • Introduction • Data properties • Laser data • Map data • Approach • Densifying 2d map • Segmentation • 3D reconstruction process (incl. processing rules) • Surface modelling • Results • Conclusions & future work

  3. Introduction • Growing demand • 3D data • Automated acquisition • Data fusion: laser data + 2d map • Now: focus on infrastructure TU Delft: Oosterom, Verbree, Penninga Research project 3D Modelling 3D Acquisition ITC Enschede: Vosselman, Oude Elberink

  4. Data properties Topographic database “TOP10NL” Object based 1:10.000 Roads, buildings, land use,… Laser scanner data “AHN” Point cloud 1 point / 9 m^2 Outlines Classification Semantics

  5. Approach - overview Segment laser data • Preprocessing data • Adding height to map points • Reconstruct new 3D polygons • Adding heights to surfaces Densify map data Interpolate laser data Detect multiple heights Add semantics Multiple levels Add laser data or knowledge

  6. Preprocessing • Laserdata • Surface growing • Seed surface detection by 3D Hough • Smooth surfaces allowed • Small segments removed • Topographic map • More map points needed in 3D

  7. Interchange in 3D Interchange in 2D Preprocessing • Laserdata • Surface growing • Seed surface detection by 3D Hough • Smooth surfaces allowed • Small segments removed • Topographic map • More map points needed in 3D

  8. Adding height to map points • Interpolation • Use laser points in nearest dominant segment • For every neighbouring object • Detect multiple heights • Add semantics • Water = horizontal • Average if close • Road = smooth

  9. Adding height to map points • Interpolation • Use laser points in nearest dominant segment • For every neighbouring object • Detect multiple heights • Add semantics • Water = horizontal • Average if close • Road = smooth

  10. Interchange in 3D Reconstruct new polygons • Multiple levels Hidden polygons New polygons

  11. Adding height to surfaces • Laser data • Add to meadow etc. • Perform morphological filtering near edges • Modelling • Roads, buildings, water

  12. Results

  13. Results

  14. Results

  15. At the moment… • Adding knowledge to program: • Merging road segments correctly • Detect & correct fusion errors automatically • Preparing 4 presentations (feedback) And the next moment… • Building reconstruction • Quality measures for 3D map

  16. Conclusions • Complex infrastructural objects can be reconstructed in 3D • New polygons are created where needed • Not yet correctly, or not yet automatically

  17. Thank you for your attention. Questions?

  18. Extra slides

  19. Extra slides

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