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CZO_SGP2020.pdf
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Accepted manuscript
Embargo End Date:
2021-08-13
Type
ArticleKAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Visual Computing Center (VCC)
KAUST Grant Number
CRG-2017-3426Date
2020-08-12Online Publication Date
2020-08-12Print Publication Date
2020-08Embargo End Date
2021-08-13Permanent link to this record
http://hdl.handle.net/10754/664764
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In this paper, we propose a novel method, which we call Consistent ZoomOut, for efficiently refining correspondences among deformable 3D shape collections, while promoting the resulting map consistency. Our formulation is closely related to a recent unidirectional spectral refinement framework, but naturally integrates map consistency constraints into the refinement. Beyond that, we show further that our formulation can be adapted to recover the underlying isometry among near-isometric shape collections with a theoretical guarantee, which is absent in the other spectral map synchronization frameworks. We demonstrate that our method improves the accuracy compared to the competing methods when synchronizing correspondences in both near-isometric and heterogeneous shape collections, but also significantly outperforms the baselines in terms of map consistency.Citation
Huang, R., Ren, J., Wonka, P., & Ovsjanikov, M. (2020). C onsistent Z oom O ut : Efficient Spectral Map Synchronization. Computer Graphics Forum, 39(5), 265–278. doi:10.1111/cgf.14084Sponsors
The authors thank the anonymous reviewers for their valuable comments. Parts of this work were supported by the KAUST OSR Award No. CRG-2017-3426 and the ERC Starting Grant No. 758800 (EXPROTEA).Publisher
WileyJournal
Computer Graphics ForumAdditional Links
https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14084ae974a485f413a2113503eed53cd6c53
10.1111/cgf.14084