We present Strokes2Surface, an offline geometry-reconstruction pipeline built upon a 4D Sketching Interface, MR.Sketch, targeted at architectural design. The pipeline recovers a curve network from designer-drawn strokes, thus bridging between concept design and digital modeling stages in architectural design. The input to our pipeline consists of 3D strokes' polyline vertices and their corresponding timestamps (as of the fourth dimension), along with additional geometric and stylus-related recorded properties. Inspired by sketch consolidation and sketch-based modeling methods, our pipeline leverages such data and combines three Machine Learning (ML) models; a classifier and two clustering models. In particular, based on observations of practices designers typically employ in architectural design sketches, we solve a binary classification problem to recognize whether a stroke depicts a boundary and edge or is used to fill in the enclosing areas and faces of the intended architectural object. Followed by the two clustering models, strokes of each type are further parsed into groups, each representing either a single edge or a single face. Next, groups representing edges are approximated with B-spline curves, followed by a topology-recovering process identifying and fixing desired connectivities between the curves forming a well-connected curve network. Next, groups representing the faces are employed to detect the cycles bounding patches in the curve network, resulting in the final surface mesh geometry of the architectural object. We confirm the usability of Strokes2Surface via a user study and further validate and compare our results against a range of reconstructions computed using alternative methods. We also introduce our manually labeled dataset of 4D architectural design sketches for further use in the community.

翻译：我们提出了Strokes2Surface——一种基于四维草图界面MR.Sketch的离线几何重建管线，专为建筑设计领域设计。该管线从设计师绘制的笔画中恢复曲线网络，从而在建筑设计中连接概念设计与数字建模阶段。管线的输入包括三维笔画的折线顶点及其对应的时间戳（第四维度），以及额外的几何与触控笔相关记录属性。受草图整理与基于草图的建模方法启发，该管线充分利用此类数据，结合三种机器学习模型：一个分类器与两个聚类模型。具体而言，基于对建筑设计草图中设计师常用实践的观察，我们解决了一个二分类问题，以识别笔画描绘的是边界与边，还是用于填充目标建筑对象的封闭区域与面。随后通过两个聚类模型，每种类型的笔画被进一步解析为组群，分别代表单条边或单个面。接着，代表边的组群用B样条曲线逼近，随后通过拓扑恢复过程识别并修正曲线间所需的连接性，形成连接良好的曲线网络。最后，利用代表面的组群检测曲线网络中包围面片的环，生成建筑对象的最终表面网格几何结构。我们通过用户研究验证了Strokes2Surface的可用性，并进一步将结果与多种替代方法计算的重建结果进行对比验证。同时，我们引入了手动标注的四维建筑设计草图数据集，以供社区进一步使用。