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Huber- L1 -based non-isometric surface registration

Research output: Contribution to journalArticlepeer-review

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Huber- L1 -based non-isometric surface registration. / Jiang, Tao; Yang, Xiaosong ; Zhang, Jianjun; Tian, Feng ; Liu, Shuang; Xiang, Nan; Qian, Kun.

In: VISUAL COMPUTER, Vol. 35, No. 6-8, 01.06.2019, p. 935-948.

Research output: Contribution to journalArticlepeer-review

Harvard

Jiang, T, Yang, X, Zhang, J, Tian, F, Liu, S, Xiang, N & Qian, K 2019, 'Huber- L1 -based non-isometric surface registration', VISUAL COMPUTER, vol. 35, no. 6-8, pp. 935-948. https://doi.org/10.1007/s00371-019-01670-1

APA

Jiang, T., Yang, X., Zhang, J., Tian, F., Liu, S., Xiang, N., & Qian, K. (2019). Huber- L1 -based non-isometric surface registration. VISUAL COMPUTER, 35(6-8), 935-948. https://doi.org/10.1007/s00371-019-01670-1

Vancouver

Jiang T, Yang X, Zhang J, Tian F, Liu S, Xiang N et al. Huber- L1 -based non-isometric surface registration. VISUAL COMPUTER. 2019 Jun 1;35(6-8):935-948. https://doi.org/10.1007/s00371-019-01670-1

Author

Jiang, Tao ; Yang, Xiaosong ; Zhang, Jianjun ; Tian, Feng ; Liu, Shuang ; Xiang, Nan ; Qian, Kun. / Huber- L1 -based non-isometric surface registration. In: VISUAL COMPUTER. 2019 ; Vol. 35, No. 6-8. pp. 935-948.

Bibtex Download

@article{9efe468af1a44c68bd568a96a5f8ff96,
title = "Huber- L1 -based non-isometric surface registration",
abstract = "Non-isometric surface registration is an important task in computer graphics and computer vision. It, however, remains challenging to deal with noise from scanned data and distortion from transformation. In this paper, we propose a Huber-L 1-based non-isometric surface registration and solve it by the alternating direction method of multipliers. With a Huber-L 1-regularized model constrained on the transformation variation and position difference, our method is robust to noise and produces piecewise smooth results while still preserving fine details on the target. The introduced as-similar-as-possible energy is able to handle different size of shapes with little stretching distortion. Extensive experimental results have demonstrated that our method is more accurate and robust to noise in comparison with the state-of-the-arts. ",
keywords = "Huber-L, Non-isometric, Surface registration",
author = "Tao Jiang and Xiaosong Yang and Jianjun Zhang and Feng Tian and Shuang Liu and Nan Xiang and Kun Qian",
year = "2019",
month = jun,
day = "1",
doi = "10.1007/s00371-019-01670-1",
language = "English",
volume = "35",
pages = "935--948",
journal = "VISUAL COMPUTER",
issn = "0178-2789",
publisher = "Springer Verlag",
number = "6-8",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Huber- L1 -based non-isometric surface registration

AU - Jiang, Tao

AU - Yang, Xiaosong

AU - Zhang, Jianjun

AU - Tian, Feng

AU - Liu, Shuang

AU - Xiang, Nan

AU - Qian, Kun

PY - 2019/6/1

Y1 - 2019/6/1

N2 - Non-isometric surface registration is an important task in computer graphics and computer vision. It, however, remains challenging to deal with noise from scanned data and distortion from transformation. In this paper, we propose a Huber-L 1-based non-isometric surface registration and solve it by the alternating direction method of multipliers. With a Huber-L 1-regularized model constrained on the transformation variation and position difference, our method is robust to noise and produces piecewise smooth results while still preserving fine details on the target. The introduced as-similar-as-possible energy is able to handle different size of shapes with little stretching distortion. Extensive experimental results have demonstrated that our method is more accurate and robust to noise in comparison with the state-of-the-arts.

AB - Non-isometric surface registration is an important task in computer graphics and computer vision. It, however, remains challenging to deal with noise from scanned data and distortion from transformation. In this paper, we propose a Huber-L 1-based non-isometric surface registration and solve it by the alternating direction method of multipliers. With a Huber-L 1-regularized model constrained on the transformation variation and position difference, our method is robust to noise and produces piecewise smooth results while still preserving fine details on the target. The introduced as-similar-as-possible energy is able to handle different size of shapes with little stretching distortion. Extensive experimental results have demonstrated that our method is more accurate and robust to noise in comparison with the state-of-the-arts.

KW - Huber-L

KW - Non-isometric

KW - Surface registration

UR - http://www.scopus.com/inward/record.url?scp=85065736871&partnerID=8YFLogxK

U2 - 10.1007/s00371-019-01670-1

DO - 10.1007/s00371-019-01670-1

M3 - Article

VL - 35

SP - 935

EP - 948

JO - VISUAL COMPUTER

JF - VISUAL COMPUTER

SN - 0178-2789

IS - 6-8

ER -

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