Surface Registration via Foliation

Xiaopeng Zheng; Chengfeng Wen; Na Lei; Ming Ma; Xianfeng Gu

doi:10.1109/ICCV.2017.107

Surface Registration via Foliation

Xiaopeng Zheng
, Chengfeng Wen
, Na Lei
, Ming Ma
, Xianfeng Gu

Computer Science

Dalian University of Technology
Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province
Stony Brook University
Capital Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

This work introduces a novel surface registration method based on foliation. A foliation decomposes the surface into a family of closed loops, such that the decomposition has local tensor product structure. By projecting each loop to a point, the surface is collapsed into a graph. Two homeomorphic surfaces with consistent foliations can be registered by first matching their foliation graphs, then matching the corresponding leaves.,,This foliation based method is capable of handling surfaces with complicated topologies and large non-isometric deformations, rigorous with solid theoretic foundation, easy to implement, robust to compute. The result mapping is diffeomorphic. Our experimental results show the efficiency and efficacy of the proposed method.

Original language	English
Title of host publication	Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	938-947
Number of pages	10
ISBN (Electronic)	9781538610329
DOIs	https://doi.org/10.1109/ICCV.2017.107
State	Published - Dec 22 2017
Event	16th IEEE International Conference on Computer Vision, ICCV 2017 - Venice, Italy Duration: Oct 22 2017 → Oct 29 2017

Publication series

Name	Proceedings of the IEEE International Conference on Computer Vision
Volume	2017-October
ISSN (Print)	1550-5499

Conference

Conference	16th IEEE International Conference on Computer Vision, ICCV 2017
Country/Territory	Italy
City	Venice
Period	10/22/17 → 10/29/17

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10.1109/ICCV.2017.107

Cite this

Zheng, X., Wen, C., Lei, N., Ma, M., & Gu, X. (2017). Surface Registration via Foliation. In Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017 (pp. 938-947). Article 8237369 (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2017-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCV.2017.107

@inproceedings{de3b86bb2d864d918d500010d553f9cd,

title = "Surface Registration via Foliation",

abstract = "This work introduces a novel surface registration method based on foliation. A foliation decomposes the surface into a family of closed loops, such that the decomposition has local tensor product structure. By projecting each loop to a point, the surface is collapsed into a graph. Two homeomorphic surfaces with consistent foliations can be registered by first matching their foliation graphs, then matching the corresponding leaves.,,This foliation based method is capable of handling surfaces with complicated topologies and large non-isometric deformations, rigorous with solid theoretic foundation, easy to implement, robust to compute. The result mapping is diffeomorphic. Our experimental results show the efficiency and efficacy of the proposed method.",

author = "Xiaopeng Zheng and Chengfeng Wen and Na Lei and Ming Ma and Xianfeng Gu",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 16th IEEE International Conference on Computer Vision, ICCV 2017 ; Conference date: 22-10-2017 Through 29-10-2017",

year = "2017",

month = dec,

day = "22",

doi = "10.1109/ICCV.2017.107",

language = "English",

series = "Proceedings of the IEEE International Conference on Computer Vision",

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booktitle = "Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017",

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Zheng, X, Wen, C, Lei, N, Ma, M & Gu, X 2017, Surface Registration via Foliation. in Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017., 8237369, Proceedings of the IEEE International Conference on Computer Vision, vol. 2017-October, Institute of Electrical and Electronics Engineers Inc., pp. 938-947, 16th IEEE International Conference on Computer Vision, ICCV 2017, Venice, Italy, 10/22/17. https://doi.org/10.1109/ICCV.2017.107

Surface Registration via Foliation. / Zheng, Xiaopeng; Wen, Chengfeng; Lei, Na et al.
Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 938-947 8237369 (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2017-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Zheng, Xiaopeng

AU - Wen, Chengfeng

AU - Lei, Na

AU - Ma, Ming

AU - Gu, Xianfeng

PY - 2017/12/22

Y1 - 2017/12/22

N2 - This work introduces a novel surface registration method based on foliation. A foliation decomposes the surface into a family of closed loops, such that the decomposition has local tensor product structure. By projecting each loop to a point, the surface is collapsed into a graph. Two homeomorphic surfaces with consistent foliations can be registered by first matching their foliation graphs, then matching the corresponding leaves.,,This foliation based method is capable of handling surfaces with complicated topologies and large non-isometric deformations, rigorous with solid theoretic foundation, easy to implement, robust to compute. The result mapping is diffeomorphic. Our experimental results show the efficiency and efficacy of the proposed method.

AB - This work introduces a novel surface registration method based on foliation. A foliation decomposes the surface into a family of closed loops, such that the decomposition has local tensor product structure. By projecting each loop to a point, the surface is collapsed into a graph. Two homeomorphic surfaces with consistent foliations can be registered by first matching their foliation graphs, then matching the corresponding leaves.,,This foliation based method is capable of handling surfaces with complicated topologies and large non-isometric deformations, rigorous with solid theoretic foundation, easy to implement, robust to compute. The result mapping is diffeomorphic. Our experimental results show the efficiency and efficacy of the proposed method.

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U2 - 10.1109/ICCV.2017.107

DO - 10.1109/ICCV.2017.107

M3 - Conference contribution

AN - SCOPUS:85041926336

T3 - Proceedings of the IEEE International Conference on Computer Vision

SP - 938

EP - 947

BT - Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th IEEE International Conference on Computer Vision, ICCV 2017

Y2 - 22 October 2017 through 29 October 2017

ER -

Surface Registration via Foliation

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