A Probabilistic Method for Fractured Cultural Relics Automatic Reassembly

Author:

Wang Haiping1,Zang Yufu2,Liang Fuxun1,Dong Zhen1,Fan Hongchao3,Yang Bisheng1

Affiliation:

1. Wuhan University, Wuhan, Hubei, China

2. Nanjing University of Information Science 8 Technology, Nanjing, Jiangsu, China

3. Norwegian University of Science and Technology, Trondheim, Norway

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.

Funder

Fundamental Research Funds for the Central Universities

National Science Fund for Distinguished Young Scholars

China Postdoctoral Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications,Information Systems,Conservation

Reference66 articles.

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1. MatchMakerNet: Enabling Fragment Matching for Cultural Heritage Analysis;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

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