IMAGE Semi-automatic 3D building extraction in dense urban areas using digital surface models Dr....
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IMAGE Semi-automatic 3D building extraction in dense urban areas using digital surface models Dr. Philippe Simard President SimActive Inc.
Transcript of IMAGE Semi-automatic 3D building extraction in dense urban areas using digital surface models Dr....
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Semi-automatic 3D building extraction in dense urban areas using digital surface models Dr. Philippe SimardPresidentSimActive Inc.
About SimActive
Founded in 2003, SimActive is the developer of Correlator3D™ software, a patented end-to-end photogrammetry solution
SimActive has been selling Correlator3D™ to leading mapping firms and government organizations around the world
Correlator3D™ is the fastest commercial software to perform DSM generation due to the GPU
DSM DTM Mosaic 3D Features
Correlator3D™ Software
DSM Generation
EO Refinement
Mosaic Creation
DEM Editing
Orthorectification
DTM ExtractionMicrosoft Ultracam
Applanix DSS
DiMAC
Intergraph Z/I DMC
VM A3 Mosaic Editing
PROCESSING MODULESIMAGERY
ADS80
Scanned Films
Aerial
GeoEye
ALOS Prism
Cartosat-1
Worldview
Quickbird
Ikonos
SPOT
Satellite
Feature Extraction
GivenElevation models
Need3D Polygons describing 3D features
ProblemHow to extract 3D features accurately and efficiently? 3D buildings
Problem Definition
ManualVery slow collection processHigh accuracyRequire highly-trained personnel Significant user interpretation required
Fully Automatic
Error proneFast
Significant editing requiredAutomatically generated results do not meet user requirements
Existing Solutions
Customer feedback: Simple buildings are easy – little time investment needed Complex buildings are a challenge – no tools exist to handle
these efficiently Market gap: how to efficiently extract complex buildings?
80% of the time is spent on 20% of the buildings Key idea: design a novel approach for quick extraction of
complex buildings
Motivation
Semi-automatic Requires simple feedback from user Creates 3D polygons in 2D space using elevation models 3D information is automatically extracted by intelligent
analysis of the data
Our Approach
DSM
Photogrammetric
LiDAR
Visual Aid
Mosaic
2D / 3D Polygons
Building footprints
Water body contours
Optional
Optional
3D Polygons
Buildings
Water bodies
Roads
Forestry
Workflow
User selects rough outline
Contour automatically fitted around building edges
3D polygons created over the selectionusing elevation data in the DSM
Roof geometry is refined by segmenting the polygon into planes
Surfaces and edges are automatically merged in the background when appropriate
How it works
Extracting Buildings
Rough selection around building Contour fitted around building edges automatically
Contour Extraction
Buildings
Roof Creation
Original surface model Extracted contour First segment to add slope
Roof details addedFinal vector polygonVectorized building model
Buildings
To help the operator, planes are automatically shaded in either red, yellow or green as roof geometry is refined
How it works: as the operator is segmenting the building polygon, the software automatically attempts to fit a plane over each new segment
Red: Bad fit Yellow: Medium fit Green: Good fit
Visual Feedback
Best Fit: Uses elevation values surrounding selected planes to determine the best fit for these planes
Rectify: Aims to create right angles (90 degrees) between close-to perpendicular vectors
Merge Surface: Combines coplanar polygons automatically
Merge Edge: Remove redundant points
Advanced Functions
Buildings
Input DSM Output building model
Photogrammetric
Accuracy: 20cm resolution; 4cm vertical Accuracy: 10cm resolution; 10cm vertical
Sample Results
LiDAR
Accuracy: 1m resolution; 10 cm vertical Accuracy: 50cm resolution; 25cm vertical
Input LiDAR DSM Output Vectors
Sample Results
Dependency: Input DSM resolution / accuracy User ability to correctly segment 3D
surfaces during 3D feature extraction Accuracy:
Horizontal: 0.5 times the GSD of DSM Vertical: 2.5 times the vertical
accuracy of DSM
Output Quality
Examples of complex buildings
Industry average: 30 seconds per complex building
SimActive average: 18 seconds per complex building
Speed
Same technology has been adapted for other features
ForestsRoadsWater Bodies
Difference: how contours and 3D values are determined
3D features
Other Extraction Modes
Fast collection process High accuracy Short learning curve Best of both worlds solution
Benefits
Image data will be used during editing to further increase accuracy
Automatic roof creation using templates Extraction of other 3D shapes (e.g. spheres, cylinders) 3D viewing
Future Developments
