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Foundations of digital sketch processing

Foundations of digital sketch processing
数字草图处理基础
批准号:
571419-2021
负责人:
Bessmeltsev, MikhailM
金额:
$3.27万
依托单位:
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
素描,即在平面上绘制曲线笔触,是传达形状的一种自然方式。专家和业余爱好者一样,无处不在地使用草图来描绘真实和虚拟的内容,包括人物、机械、分子和抽象形状。因此,素描既是一种艺术形式,也是人与人之间形状交流的媒介,并提供了一种在人类用户和计算机系统之间交流形状的途径。现有的草图处理系统不能处理复杂的、不精确的草图,而通常是针对干净的图纸。我们研究的长期目标是开发数字草图处理算法,该算法将为未来用于2D/3D内容创建的健壮的草图处理系统奠定基础。在追求这一目标的过程中,我们将双管齐下,为两个目标服务:我们将创建算法和系统,将草图视为一种艺术形式,即帮助人类提高他们绘制的草图的质量,以及2)草图作为形状表示,即使人类能够使用草图进行人机交流。1.作为艺术形式的素描。在我们的第一线研究中,我们将开发算法,帮助人类改进他们的素描,创造数字艺术。我们将利用艺术文学和人类感知理论(如格式塔心理学)中的感知原理,在算法上提高人类绘制内容的清晰度、美感和表现力。特别是,我们将创建基于子笔画分析和区域提取的与样式无关的草图合并。我们将开发算法来给草图上色和着色。2.作为形状表示的草图。在我们的第二条研究路线中,我们将通过草图促进人机交流,即使用草图将2D/3D形状传达给内容创作系统。我们将使用草图解决现代系统不稳定的根本原因,通过草图实现更强大的2D卡通动画和3D内容建模系统。我们将开发几何处理工具包,将草图视为底层几何图形的近似描述,类似于点云或网格近似底层曲面的方式。我们将使用边界元方法对草图上的拉普拉斯算子进行离散化,使最先进的基于拉普拉斯的方法能够变形或找到几何之间的对应关系,以便将来进行变形和插入系统。我们将分析绘制草图时人的不准确之处,并创建从粗略草图推断图纸拓扑的算法。这将使拓扑敏感系统(例如,基于草图的建模)能够正确解释复杂的自然草图。我们将使用草图作为蚀刻来将纹理/阴影/阴影、毛发/头发传达到表面。PI对于这项研究是独一无二的:它需要基于感知的研究和优化的专业知识(Sheffer教授),数学/离散微分几何专业知识(Bessmeltsev教授),以及渲染、阴影和纹理方面的专业知识(Poulin教授)。Sheffer教授和Bessmeltsev教授在草图处理/建模方面都有丰富的出版记录,包括5份共享出版物,Sheffer教授和Poulin教授分享了1篇关于体积建模的论文。可能的结果是加拿大所需应用领域的算法和系统,特别是魁北克、电影/动画/游戏和制造业,其中内容创建是主要的耗时和费力的任务之一。我们将使用素描促进更强大、更高效的内容创作系统,让艺术家和设计师将他们的时间集中在创造性任务上。
英文摘要
Sketching, or drawing of curved strokes on a flat surface, is a natural way to communicate shapes. Experts and amateurs alike ubiquitously employ sketches to depict both real and virtual content, including characters, machinery, molecules, and abstract shapes. As such sketches serve as both an art form and a medium for inter-human shape communication, and offer an avenue to communicate shapes between human users and computer systems. Existing systems for sketch processing are not capable of processing complex, imprecise sketches instead typically targeting clean drawings.The long-term goal of our research is to develop digital sketch processing algorithms that will form the foundation of future robust sketch processing systems for 2D/3D content creation. In pursuing that goal, we will take a two-pronged approach serving two targets: We will create algorithms and systems viewing 1)Sketches as an Art Form, i.e. assisting humans in improving the quality of the sketches they draw, and 2) Sketches as Shape Representation, i.e. enabling humans to use sketches for human-computer communication. 1.Sketch As Art Form. In our first line of research, we will develop algorithms assisting humans to improve their sketches, creating digital art. We will algorithmically improve clarity, aesthetics, and expressivity of human drawn content,leveraging the perceptual principles from artistic literature and human perception theories,e.g. Gestalt psychology. In particular, we will create a style-independent sketch consolidation based on sub-stroke analysis and region extraction. We will develop algorithms to colorize and shade sketches. 2.Sketch As Shape Representation. In our second line of research, we will facilitate human-computer communication via sketches,i.e. using sketches to communicate 2D/3D shapes to content creation systems. We will address the fundamental causes of instabilities of modern systems using sketches, enabling more robust systems for 2D cartoon animation and 3D content modeling via sketches. We will develop the geometry processing toolkit viewing rough sketch as an approximate depiction of the underlying geometry, similar to how point clouds or meshes approximate an underlying surface. We'll use Boundary Element Methods to discretize Laplacian operator on sketches, enabling state-of-the-art Laplacian-based methods to deform or find correspondences between geometries for future morphing and inbetweening systems. We will analyse human inaccuracies when drawing sketches and create algortihms inferring drawing topology from a rough sketch. This will enable topology-sensitive systems (e.g sketch-based modeling) to correctly interpret complex natural sketches. We'll use sketches as etchings to convey textures/shading/shadows, fur/hair, to surfaces.The PIs are uniquely positioned for this research: it requires expertise of perception-based research and optimization (Prof.Sheffer), in mathematics/discrete differential geometry (Prof.Bessmeltsev), and in rendering,shading,texturing (Prof. Poulin). Both Profs.Sheffer and Bessmeltsev have an extensive publication record in sketch processing/modeling, including 5 shared publications, Profs.Sheffer and Poulin shared 1 paper on volume modeling.Tangible outcome will be algorithms and systems in the area of applications required by Canadian, in particular Quebec, film/animation/gaming and manufacturing industries, where content creation is one of the main time-consuming and laborious tasks. We will facilitate more robust and efficient content creation systems using sketches, allowing artists and designers to focus their time on creative tasks.
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