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Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University 3D Modeling of Historic Sites Using Range and Image Data

Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

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Page 1: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu

Dept. of Computer Science, Columbia University Dept. of Computer Science, Hunter College, CUNY*

3D Modeling of Historic Sites Using Range and Image Data

Page 2: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

•Sites are subject to erosion, wear, vandalism•Moving targets: many phases of construction, damage and repair over many years

•Need to track changes, foresee structural problems

•Modeling allows a wider audience to ”virtually” see and tour these sites

•Our Focus: methods that can reduce modeling time using automatic methods

Preserving Cultural Heritage Sites

Page 3: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Cathedral St. Pierre, Beauvais, France

Page 4: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Modeling the CathedralGoals:

• Cathedral on the World Monuments Fund's Most Endangered List.

• Create 3-D model to examine weaknesses in the building and proposed remedies

• Establish baseline for condition of Cathedral

• Visualize the building in previous contexts

• Basis for a new collaborative way of teaching about historic sites, in the classroom and on the Internet.

Page 5: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

• Commissioned in 1225 by Bishop Milon de Nanteuil

• Only the choir and transepts were completed - choir in 1272

• In 1284 part of the central vault collapsed

• Area where the nave and façade would be is still occupied by the previous church constructed just before 1000.

• Completed in 16th century, the transept was crowned by an ambitious central spire that allowed the cathedral to rival its counterpart in Rome.

• The tower collapsed on Ascension Day in 1573.

History: 1200 - 1600

Page 6: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Rendition of original central

spire

Page 7: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

• Cathedral survived intense incendiary bombing that destroyed much of Beauvais in WW II.

• Between 1950-80 many critical iron ties were removed from the choir buttresses in a damaging experiment.

• Temporary tie-and-brace system installed in the 1990s may have made the cathedral too rigid, increasing rather than decreasing stresses upon it.

• There continues to be a lack of consensus on how to conserve the essential visual and structural integrity of this Gothic wonder.

History: 20th Century

Page 8: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Problems with the Structure

• Wind Oscillation from English Channel winds

• Strange inner and outer aisle construction – can cause rotational moments in the structure

• Leaking Roof, foundation is settling

• Built in 3 campaigns over hundreds of years with differing attention to detail

Page 9: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Time-Lapse Image - Spire Movement Due to Wind

Page 10: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Technical Challenges

• Create Global and coherent geometric models: handle full range of geometries

• Reducing data complexity

• Registration of MANY million point data sets

• Range and intensity image fusion

Page 11: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Beauvais Cathedral: Exterior Scanning Session

Page 12: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Beauvais Cathedral: Interior

Page 13: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Beauvais Cathedral: Interior Scanning Session

Page 14: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Exterior: Raw Range Scan

Page 15: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Beauvais: Scan Detail

Page 16: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Range Registration

3 Step Process:

1. Pairwise registration between overlapping scans. Match 3D lines in overlapping range images.

2. Global registration using graph search to align all scans together.

3. Multi-scan simultaneous ICP registration algorithm (Nishino et. al.)

Produces accurate registration.

Page 17: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Segmentation Algorithm

• Creates reduced data sets (~80%).• Fit local plane to neighborhood of range points.• Classify range points: planar, non-planar, unknown.• Merge into connected clusters of co-planar points.• Identify boundaries of planes. • Used to find prominent linear features for matching.

Page 18: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

N N1 2

P P1 2

R12

Patches fit around points P1 and P2

P1 and P2 are coplanar if:

• a=cos (N1 . N2) < angle threshold• d=max(|R12 N1|, |R12 N2|) < distance threshold

-1

Local Planarity Comparison

Page 19: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Segmentation and 3-D Registration Lines

Page 20: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Pairwise Registration of Scans: Overview

• Segmenter creates planes and associated boundary lines

• Matching lines in 2 scans can be problematic

• Attributes of lines serve as a good filter for matching lines: length of lines, area of planar region that line bounds

• Use pairs of matched lines to compute transform

• Transform each line in one scan to the other. Results are graded by metric of number of matched lines after transform

• Choose best graded transform

Page 21: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Pairwise Registration

Page 22: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Registered Scans – Beauvais Cathedral

Page 23: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Global Registration

Page 24: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Graph Search Global Registration• Create weighted graph of scans. Edges of graph are confidence in finding correct registration between pairs of scans

• Confidence (cost) is number of correctly aligned lines after applying registration (R,T)

• Global Registration: find max-cost path from pivot scan to each scan

Page 25: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Final ICP Registration

Page 26: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer
Page 27: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer
Page 28: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Beauvais Cathedral Model: Fly-Thru

Page 29: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Inside-Out: Beauvais Cathedral

Page 30: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Texture Mapped Models

Page 31: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Texture Mapped Models

Page 32: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Texture Mapped Models

Page 33: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Automating the Process:

•Robot can serve as a sensor platform containing ranging and imaging devices

•Onboard sensors can register sensor data with the environment: GPS, Odom., Vision

•Given a 2-D map of an environment, robot can augment 2-D map with 3-D models

•Planner can interact with robot navigator to move to new viewing sites

Build a Mobile Site Modeling Robot

Page 34: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

GPS

DGPSScanner

Network

Camera

PTUCompass

The AVENUE Mobile Platform

UTONOMOUS

EHICLE FOR

XPLORATION AND

AVIGATION IN

RBAN

NVIRONMENTS

PC

Sonars

Page 35: Peter Allen, Ioannis Stamos*,Alejandro Troccoli, Ben Smith, Marius Leordeanu*, Y.C. Hsu Dept. of Computer Science, Columbia University Dept. of Computer

Future Work

• Continue to automate the model building process

• Real-time texture mapping for realistic walk-throughs

• View planning: finding the right viewpoints and number of views

• Incorporate sensor planning with robot path planning to plan next view

• Modeling with non-planar segments.

• Merging multiple overlapping photos.