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A Probabilistic Method for Fractured Cultural Relics Automatic Reassembly

Authors:

Bisheng YangAuthors Info & Claims

Journal on Computing and Cultural Heritage (JOCCH), Volume 14, Issue 1

Article No.: 5, Pages 1 - 25

https://doi.org/10.1145/3417711

Published: 22 January 2021 Publication History

Abstract

Masses of fragile cultural relics are dug out in fragments due to long-standing burying and their fragility, which must be reassembled to play a role in cultural heritage study. However, it is very challenging to automatically reassemble a large collection of fragments of unknown geometric shapes. In this article, a novel probabilistic method for fractured cultural relics automatic reassembly is proposed to solve the problem in terms of good accuracy, efficiency, and robustness. First, a set of matching units are detected and described by the 2D Link-Chain Descriptors (LCD) and the 3D Spatial-Distribution Descriptors (SDD). Second, the pairwise reassembly probability is calculated by combining the similarities of LCD and SDD descriptors, then the collision detection is conducted to eliminate the incorrect overlapping pairs. Finally, a global optimal reassembly solution is obtained by iterative graph optimization with the constrains of the loop-closures and overlap restrictions. Comprehensive experiments with eight challenging datasets demonstrate that the proposed method achieved good performance in terms of minor reassembly errors, efficiency and robustness to noise, varying point density and completeness.

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Cited By

Hayon OMünger SShimshoni ITal A(2024)ArcAid: Analysis of Archaeological Artifacts using Drawings2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00710(7249-7259)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00710
Xu WJiang ZGuo YJi XGuo ZLiu YXiao X(2024)Registration of Airborne LiDAR Bathymetry Seafloor Point Clouds Based on the Adaptive Matching of Corresponding PointsIEEE Geoscience and Remote Sensing Letters10.1109/LGRS.2024.336641621(1-5)Online publication date: 2024
https://doi.org/10.1109/LGRS.2024.3366416
Xiong MShi ZZhou XZhang YZhang S(2024)Gmd: Gaussian mixture descriptor for pair matching of 3D fragmentsMultimedia Systems10.1007/s00530-024-01519-130:6Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s00530-024-01519-1
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Index Terms

A Probabilistic Method for Fractured Cultural Relics Automatic Reassembly
1. Applied computing
  1. Arts and humanities
    1. Fine arts
2. Computing methodologies
  1. Computer graphics
    1. Shape modeling
      1. Point-based models
      2. Shape analysis

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Published In

cover image Journal on Computing and Cultural Heritage

Journal on Computing and Cultural Heritage Volume 14, Issue 1

February 2021

200 pages

ISSN:1556-4673

EISSN:1556-4711

DOI:10.1145/3446566

Editor:
Franco Niccolucci
VAST-LAB at PIN, University of Florence, Italy

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Copyright © 2021 ACM.

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Publication History

Published: 22 January 2021

Accepted: 01 August 2020

Revised: 01 June 2020

Received: 01 February 2020

Published in JOCCH Volume 14, Issue 1

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Cited By

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https://doi.org/10.1109/WACV57701.2024.00710
Xu WJiang ZGuo YJi XGuo ZLiu YXiao X(2024)Registration of Airborne LiDAR Bathymetry Seafloor Point Clouds Based on the Adaptive Matching of Corresponding PointsIEEE Geoscience and Remote Sensing Letters10.1109/LGRS.2024.336641621(1-5)Online publication date: 2024
https://doi.org/10.1109/LGRS.2024.3366416
Xiong MShi ZZhou XZhang YZhang S(2024)Gmd: Gaussian mixture descriptor for pair matching of 3D fragmentsMultimedia Systems10.1007/s00530-024-01519-130:6Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1007/s00530-024-01519-1
Wang YYu HGao WXia YNduka C(2023)MGEED: A Multimodal Genuine Emotion and Expression Detection DatabaseIEEE Transactions on Affective Computing10.1109/TAFFC.2023.328635115:2(606-619)Online publication date: 15-Jun-2023
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Villegas-Suarez ALopez CSipiran I(2023)MatchMakerNet: Enabling Fragment Matching for Cultural Heritage Analysis2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)10.1109/ICCVW60793.2023.00178(1624-1633)Online publication date: 2-Oct-2023
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Lamb NBanerjee SBanerjee N(2022)DeepMend: Learning Occupancy Functions to Represent Shape for RepairComputer Vision – ECCV 202210.1007/978-3-031-20062-5_25(433-450)Online publication date: 23-Oct-2022
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