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주경돈

Joo, Kyungdon
Robotics and Visual Intelligence Lab.
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FRACTURE ASSEMBLY WITH SEGMENTATION AND ITERATIVE REGISTRATION

Author(s)
Kim, JinhyeokLee, InhaJoo, Kyungdon
Issued Date
2024-04-15
DOI
10.1109/ICASSP48485.2024.10447659
URI
https://scholarworks.unist.ac.kr/handle/201301/84814
Citation
IEEE International Conference on Acoustics, Speech and Signal Processing, pp.6945 - 6949
Abstract
Reassembling broken fractures back to their original shape remains a complex challenge. While prior research has demonstrated impressive results in domain-specific assembly, these methods largely depend on human-designed structural priors or struggle with assembling diverse shapes. To tackle this issue, we introduce a new fracture assembly framework based on segmentation and iterative registration, so-called FRASIER. By finding broken regions of fractures by segmentation, FRASIER dramatically increases overlap region ratios between fractures, which allows us to align fractures by registration. In addition, we employ point cloud XOR and beam search to make our framework robust. Experiments demonstrate that FRASIER outperforms state-of-the-art methods. Project page: https://frasier-assembly.github.io.
Publisher
Institute of Electrical and Electronics Engineers Inc.

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