Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling

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2 Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling EMRE ÖZDEMİR 1,2, Fabio Remondino 1 1 3D Optical Metrology unit Bruno Kessler Foundation (FBK) Trento, Italy eozdemir@fbk.eu remondino@fbk.eu 2 Space Center Skolkovo Institute of Science and Technology (SKOLTECH), Moscow, Russia

3 Motivation Ø Importance of 3D City Models: 3D cadaster, urban planning, energy, disaster management Ø 3D Building Models: - Essential, - Needed in high accuracy for 3DCM Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 3

4 Current Trends & Risks Existing models/approaches for 3DBM, brief look in 2 categories: Procedural Modeling: - Set of rules (location, dimensions, ) - High data compression - Lower metric accuracy Reality-based Modeling: - 3D surveying techniques, Derive 3D geometry from 3D data - High metric accuracy - Ancillary data: DEM Roof types Footprints Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 4

5 Current Trends & Risks Ø Ancillary data not always: Up-to-date Reliable Reachable Ø Existing methodologies not exploiting the accuracy potential of sensors (Rottensteiner et al., 2014) A new method aiming: Not needing ancillary data Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 5

6 Aim of the Study Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 6

7 Aim of the Study Our method aiming to produce 3DBM with: Ø No ancillary data (footprints, roof types, etc.) Ø Segmentation of: - Orthophoto (for vegetation mask) - Point cloud (for classification: 4 Classes) Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 7

8 Proposed Method Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 8

9 Proposed Method Vegetation (Grass & Trees) Others (GLOs & Buildings) Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 9

10 Preliminary Results Orthophoto: x cm Point Cloud: 53million pts, ( 50 pts/sqm), Dortmund, ISPRS Benchmark dataset Masking the point cloud 6 hours** Region growing segmentation 7 hours** **Using a mid-class laptop Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 10

11 Preliminary Results Orthophoto: x cm Point Cloud: 33million pts, ( 30 pts/sqm) Bergamo Città Alta Masking the point cloud 6 hours** Region growing segmentation 7 hours** **Using a mid-class laptop Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 11

12 Preliminary Results Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 12

13 Conclusions Proposed method: Ø Generation of vegetation mask from orthophoto, Ø Clustering with Kohonen s SOM Ø Segmentation and classification of separated point clouds, Ø Ø 3D Region Growing for segmentation (Point Cloud Library) Manually picking segments for classification Ø 3D reconstruction Ø Ø Mapple and PolyFit for 3D model generation** Manual transfer of data from previous step (for now) **Special thanks to Dr. Liangliang Nan (3D Geoinformatics, TU Delft) for his kind support Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 13

14 Future Work Next steps for our ongoing study: Ø Ground truth & accuracy assessment for: Classification & 3DBM Ø Quicker vegetation masking directly on the point cloud Ø Automation of moving from segmentation to classification Ø Custom algorithm for 3DBM generation from point cloud classification output Ø Collect all the progress in one platform Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling 14

15 3D Optical Metrology unit Bruno Kessler Foundation (FBK) Trento, Italy Emre Özdemir, Fabio Remondino - Segmentation of 3D Photogrammetric Point Cloud for 3D Building Modeling