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A System for High-Volume Acquisition and Matching of Fresco Fragments Reassembling Theran Wall Paintings. Benedict Brown 1,2 , Corey Toler-Franklin 1 , Diego Nehab 1,3 , Michael Burns 1 , Andreas Vlachopoulos 4 , Christos Doumas 4,5 , David Dobkin 1 , Szymon Rusinkiewicz 1 , Tim Weyrich 1,6.
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A System forHigh-Volume Acquisition and Matching of Fresco FragmentsReassembling Theran Wall Paintings Benedict Brown1,2, Corey Toler-Franklin1, Diego Nehab1,3,Michael Burns1, Andreas Vlachopoulos4, Christos Doumas4,5,David Dobkin1, Szymon Rusinkiewicz1, Tim Weyrich1,6 1Princeton University 3Microsoft Research 5National University of Athens 2Katholieke Universiteit Leuven 4Akrotiri Excavations, Thera 6University College, London
Bronze Age Thera • Modern day Santorini • Aegean civilization: c. 1700 BC • Traded with other Mediterranean civilizations • Evidence of fishing, agriculture, and livestock • Volcanic eruption c. 1650 BC NASA Visible Earth
Akrotiri • Major archaeological excavation since 1967 • Well-preserved by ash • Most significant find: plaster wall paintings • Pigments excellently preserved Thera Foundation
Akrotiri • Major archaeological excavation since 1967 • Well-preserved by ash • Most significant find: plaster wall paintings • Pigments excellently preserved • But shattered in pieces by earthquake
The Akrotiri Jigsaw • Current assembly process is laborious
The Akrotiri Jigsaw • Current assembly process is laborious • Enough work for another century
Fragment Characteristics Conservators consider: size, thickness level of erosion discoloration and fading set of pigments curvature / flatness texture of the back string impressions
Constrained 3-D Acquisition Protocol • Automatic turntable control • Acquire scans at 45° • Two 360°scan sequences • Face-down: front face at known plane • Face-up: front face visible
Color and Normals: 2-D Acquisition • Custom scan software • One-click acquisition • Preview scan locates fragment • Five scans • Four front orientations (photometric normals) • One back orientation
Scan Alignment with Multi-Way ICP • Align fragments scanned on turntable • Axis of rotation gives initial guess • Standard algorithm to improve alignments:Iterative Closest Points [Besl 1992], [Chen 1992] • Flat front surfaces lead to instability • Improved algorithm: Multi-way ICP • Constrain all scan-to-scantransformations to be identical • Equivalent to solving fora single rotation axis
Front/Back Alignment • Flipping fragment is uncalibrated • Little overlap between front and back scans • Front/back alignment is vertically unstable
Front/Back Alignment • Use front face to determinevertical alignment • Visible in front scans • On (calibrated) turntablesurface in back scans • Initial guess and ICP forwithin-plane alignment
2-D/3-D Alignment • Flatbed scanner has superior color • Can’t use calibration [Levoy 2000], reliable silhouette [Lensch 2000], or features [Liu 2006][Chen 2007] • Use image alignment: PCA + downhill simplex Projected 3-D Color Flatbed Scan
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Ribbon Matching • Try all possible alignments • Update alignment incrementally • Regular edge parameterization:similar to image correlation
Fragment Matching ICP Matching • Nearest neighbor correspondence search • Iterate to find matches • 45 seconds per fragment pair Ribbon Matching • Regular edge sampling for correspondences • Exhaustive search with incremental update • 2 seconds per pair Original (irregular) mesh Resampled ribbon
Erosion Detection • Erosion causes incorrect alignments • Detected on ribbons with normal constraint Fragment Front No Erosion Detection Fragment Back
Erosion Detection • Erosion causes incorrect alignments • Detected on ribbons with normal constraint Fragment Front No Erosion Detection With Erosion Detection Fragment Back
Outline • System design • Processing pipeline • Matching • Results
Synthetic Fresco 25 mm strip width 12.5 mm strip width 50 mm strip width
Future Work (Matching) • Multi-cue matching • Improved ribbon matching/Handling gaps • Dynamic programming can probablyhandle gaps • Record all possible alignments instead of only best candidates to do saliency analysis • Global matching • Fuse matched fragments and re-match • Do global consistency checks on networks of matches
Future Work (Scanners) We want to scan: • large fragments • assembled edges? • edge and back normals Approach: • Hand-held scanner • Two cameras and a projector/fixed pattern • Alignment similar to in-hand scanner • Should be able to get normals from mutiple views
Future Work (Scanners) We want to scan: • large fragments • assembled edges? • edge and back normals Approach: • Hand-held scanner • Two cameras and a projector/fixed pattern • Alignment similar to in-hand scanner • Should be able to get normals from mutiple views
Acknowledgments • Princeton University: Tom Funkhouser, Dimitris Gondicas,Matt Plough, Phil Shilane, Xiaojuan Ma • Akrotiri Excavation, Laboratory of Wall Paintings:Manolis Hamaoui, Litsa Kalambouki, Marina Papapetrou, Panagiotis Vlachos, Alexandros Zokos, Iakovos Michailidis, Fragoula Georma, Niki Spanou • Special thanks to David Koller (University of Viriginia),Misha Kazhdan (Johns Hopkins University), and Peter Nomikos Jr. • Funding: Thera Foundation, Kress Foundation,Seeger Foundation, Cotsen Family Foundation, andNSF Grants CCF-0347427 and CCF-0702580