IMAGE Semi-automatic 3D building extraction in dense urban areas using digital surface models Dr. Philippe Simard President SimActive 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 DSMDTMMosaic3D Features

Correlator3D™ Software DSM Generation EO Refinement Mosaic Creation DEM Editing Orthorectification DTM Extraction Microsoft Ultracam Applanix DSS DiMAC Intergraph Z/I DMC VM A3 Mosaic Editing PROCESSING MODULES IMAGERY ADS80 Scanned Films Aerial GeoEye ALOS Prism Cartosat-1 Worldview Quickbird Ikonos SPOT Satellite Feature Extraction

Given Elevation models Need 3D Polygons describing 3D features Problem How to extract 3D features accurately and efficiently? 3D buildings Problem Definition

Manual Very slow collection process High accuracy Require highly-trained personnel Significant user interpretation required Fully Automatic Error prone Fast Significant editing required Automatically 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 3D Polygons Buildings Water bodies Roads Forestry Workflow

 User selects rough outline  Contour automatically fitted around building edges  3D polygons created over the selection using 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 buildingContour fitted around building edges automatically Contour Extraction Buildings

Roof Creation Original surface modelExtracted contourFirst segment to add slope Roof details added Final vector polygon Vectorized 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 fitYellow: Medium fitGreen: 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 DSMOutput building model Photogrammetric Accuracy: 20cm resolution; 4cm verticalAccuracy: 10cm resolution; 10cm vertical Sample Results

LiDAR Accuracy: 1m resolution; 10 cm verticalAccuracy: 50cm resolution; 25cm vertical Input LiDAR DSMOutput 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  Forests  Roads  Water 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

Dr Philippe Simard President SimActive Inc. Tel.: ext. 21 Fax: Thank You