An adaptive floating tangents fitting with helices method for image-based hair modeling

Yongtang Bao; Yue Qi

doi:10.1145/3095140.3095166

An adaptive floating tangents fitting with helices method for image-based hair modeling

Yongtang Bao
, Yue Qi^*

^*Corresponding author for this work

School of Computer Science and Engineering

Beihang University

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

2 Scopus citations

Abstract

Currently, hair geometry is mostly represented as sequences of 3D points. It is difficult to simulate hair directly from this representation. This paper proposes a novel approach to convert hair geometry model into helices, which could be easily plugged into dynamic hair simulation. We construct a hair model from a hybrid orientation field. Then we use adaptive floating tangents fitting algorithm to convert this hair geometry model into a physics-based hair model. We simulate dynamic hair by Lagrange equations. Results show that this approach can preserve structural details of 3D hair models, and can be applied to simulate various hair geometries.

Original language	English
Title of host publication	CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450352284
DOIs	https://doi.org/10.1145/3095140.3095166
State	Published - 27 Jun 2017
Event	2017 Computer Graphics International Conference, CGI 2017 - Yokohama, Japan Duration: 27 Jun 2017 → 30 Jun 2017

Publication series

Name	ACM International Conference Proceeding Series
Volume	Part F128640

Conference

Conference	2017 Computer Graphics International Conference, CGI 2017
Country/Territory	Japan
City	Yokohama
Period	27/06/17 → 30/06/17

Keywords

Adaptive floating tangents fitting
Dynamic hair simulation
Hair modeling
Hybrid orientation field

Access to Document

10.1145/3095140.3095166

Cite this

@inproceedings{2a4a579d0ff348c49727e39b8c60ffc2,

title = "An adaptive floating tangents fitting with helices method for image-based hair modeling",

abstract = "Currently, hair geometry is mostly represented as sequences of 3D points. It is difficult to simulate hair directly from this representation. This paper proposes a novel approach to convert hair geometry model into helices, which could be easily plugged into dynamic hair simulation. We construct a hair model from a hybrid orientation field. Then we use adaptive floating tangents fitting algorithm to convert this hair geometry model into a physics-based hair model. We simulate dynamic hair by Lagrange equations. Results show that this approach can preserve structural details of 3D hair models, and can be applied to simulate various hair geometries.",

keywords = "Adaptive floating tangents fitting, Dynamic hair simulation, Hair modeling, Hybrid orientation field",

author = "Yongtang Bao and Yue Qi",

note = "Publisher Copyright: {\textcopyright} 2017 ACM.; 2017 Computer Graphics International Conference, CGI 2017 ; Conference date: 27-06-2017 Through 30-06-2017",

year = "2017",

month = jun,

day = "27",

doi = "10.1145/3095140.3095166",

language = "英语",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery ",

booktitle = "CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference",

address = "美国",

}

Bao, Y & Qi, Y 2017, An adaptive floating tangents fitting with helices method for image-based hair modeling. in CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference., a26, ACM International Conference Proceeding Series, vol. Part F128640, Association for Computing Machinery , 2017 Computer Graphics International Conference, CGI 2017, Yokohama, Japan, 27/06/17. https://doi.org/10.1145/3095140.3095166

An adaptive floating tangents fitting with helices method for image-based hair modeling. / Bao, Yongtang; Qi, Yue.
CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference. Association for Computing Machinery , 2017. a26 (ACM International Conference Proceeding Series; Vol. Part F128640).

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

TY - GEN

T1 - An adaptive floating tangents fitting with helices method for image-based hair modeling

AU - Bao, Yongtang

AU - Qi, Yue

PY - 2017/6/27

Y1 - 2017/6/27

N2 - Currently, hair geometry is mostly represented as sequences of 3D points. It is difficult to simulate hair directly from this representation. This paper proposes a novel approach to convert hair geometry model into helices, which could be easily plugged into dynamic hair simulation. We construct a hair model from a hybrid orientation field. Then we use adaptive floating tangents fitting algorithm to convert this hair geometry model into a physics-based hair model. We simulate dynamic hair by Lagrange equations. Results show that this approach can preserve structural details of 3D hair models, and can be applied to simulate various hair geometries.

AB - Currently, hair geometry is mostly represented as sequences of 3D points. It is difficult to simulate hair directly from this representation. This paper proposes a novel approach to convert hair geometry model into helices, which could be easily plugged into dynamic hair simulation. We construct a hair model from a hybrid orientation field. Then we use adaptive floating tangents fitting algorithm to convert this hair geometry model into a physics-based hair model. We simulate dynamic hair by Lagrange equations. Results show that this approach can preserve structural details of 3D hair models, and can be applied to simulate various hair geometries.

KW - Adaptive floating tangents fitting

KW - Dynamic hair simulation

KW - Hair modeling

KW - Hybrid orientation field

UR - https://www.scopus.com/pages/publications/85025475080

U2 - 10.1145/3095140.3095166

DO - 10.1145/3095140.3095166

M3 - 会议稿件

AN - SCOPUS:85025475080

T3 - ACM International Conference Proceeding Series

BT - CGI 2017 - Proceedings of the 2017 Computer Graphics International Conference

PB - Association for Computing Machinery

T2 - 2017 Computer Graphics International Conference, CGI 2017

Y2 - 27 June 2017 through 30 June 2017

ER -

An adaptive floating tangents fitting with helices method for image-based hair modeling

Abstract

Publication series

Conference

Keywords

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