3D打印头发造型,从发丝级别发型

IF 2.5 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING Graphical Models Pub Date : 2022-05-01 DOI:10.1016/j.gmod.2022.101135
Han Chen, Minghai Chen, Lin Lu
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引用次数: 0

摘要

个性化小雕像的设计和制造的最新进展使普通用户可以通过3D打印技术创造出高质量的小雕像。头发在获得雕像的真实感方面起着重要作用。现有的毛发重建方法存在对采集设备的高需求,或者结果非常粗略地近似。我们提出了一种新的表面重建方法,从发丝级别的发型中生成具有几何特征的3D可打印头发模型,从而将现有的数字头发数据库转换为3D可打印数据库,而不是通过扫描设备为雕像创建头发。给定一个发束级别的头发模型,我们通过发束聚类过滤发束,保留主要特征,并分两个阶段重建发束。首先,我们的算法是根据头发的结构提取头发轮廓表面并计算每个顶点的法线的关键。接下来,通过泊松曲面重建,获得了一个具有几何细节和嵌入方向场的闭合流形三角形网格。我们在没有用户互动的情况下获得了封闭的多种发型,有利于个性化的雕像制作。我们通过展示大量的例子来验证我们的方法的可行性。
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3D Printed hair modeling from strand-level hairstyles

Recent advances in the design and fabrication of personalized figurines have made the creation of high-quality figurines possible for ordinary users with the facilities of 3D printing techniques. The hair plays an important role in gaining the realism of the figurines. Existing hair reconstruction methods suffer from the high demand for acquisition equipment, or the result is approximated very coarsely. Instead of creating hairs for figurines by scanning devices, we present a novel surface reconstruction method to generate a 3D printable hair model with geometric features from a strand-level hairstyle, thus converting the exiting digital hair database to a 3D printable database. Given a strand-level hair model, we filter the strands via bundle clustering, retain the main features, and reconstruct hair strands in two stages. First, our algorithm is the key to extracting the hair contour surface according to the structure of strands and calculating the normal for each vertex. Next, a close, manifold triangle mesh with geometric details and an embedded direction field is achieved with the Poisson surface reconstruction. We obtain closed-manifold hairstyles without user interactions, benefiting personalized figurine fabrication. We verify the feasibility of our method by exhibiting a wide range of examples.

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来源期刊
Graphical Models
Graphical Models 工程技术-计算机:软件工程
CiteScore
3.60
自引率
5.90%
发文量
15
审稿时长
47 days
期刊介绍: Graphical Models is recognized internationally as a highly rated, top tier journal and is focused on the creation, geometric processing, animation, and visualization of graphical models and on their applications in engineering, science, culture, and entertainment. GMOD provides its readers with thoroughly reviewed and carefully selected papers that disseminate exciting innovations, that teach rigorous theoretical foundations, that propose robust and efficient solutions, or that describe ambitious systems or applications in a variety of topics. We invite papers in five categories: research (contributions of novel theoretical or practical approaches or solutions), survey (opinionated views of the state-of-the-art and challenges in a specific topic), system (the architecture and implementation details of an innovative architecture for a complete system that supports model/animation design, acquisition, analysis, visualization?), application (description of a novel application of know techniques and evaluation of its impact), or lecture (an elegant and inspiring perspective on previously published results that clarifies them and teaches them in a new way). GMOD offers its authors an accelerated review, feedback from experts in the field, immediate online publication of accepted papers, no restriction on color and length (when justified by the content) in the online version, and a broad promotion of published papers. A prestigious group of editors selected from among the premier international researchers in their fields oversees the review process.
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