We present Strokes2Surface, an offline geometry reconstruction pipeline that recovers well-connected curve networks from imprecise 4D sketches to bridge concept design and digital modeling stages in architectural design. The input to our pipeline consists of 3D strokes' polyline vertices and their timestamps as the 4th dimension, along with additional metadata recorded throughout sketching. Inspired by architectural sketching practices, our pipeline combines a classifier and two clustering models to achieve its goal. First, with a set of extracted hand-engineered features from the sketch, the classifier recognizes the type of individual strokes between those depicting boundaries (Shape strokes) and those depicting enclosed areas (Scribble strokes). Next, the two clustering models parse strokes of each type into distinct groups, each representing an individual edge or face of the intended architectural object. Curve networks are then formed through topology recovery of consolidated Shape clusters and surfaced using Scribble clusters guiding the cycle discovery. Our evaluation is threefold: We confirm the usability of the Strokes2Surface pipeline in architectural design use cases via a user study, we validate our choice of features via statistical analysis and ablation studies on our collected dataset, and we compare our outputs against a range of reconstructions computed using alternative methods.

翻译：本文提出Strokes2Surface，一种离线几何重建流程，旨在从非精确的4D草图中恢复连接良好的曲线网络，以弥合建筑设计中的概念设计与数字建模阶段。流程的输入包含三维笔划的折线顶点及其作为第四维度的时间戳，以及草图绘制过程中记录的附加元数据。受建筑草图绘制实践的启发，本流程结合一个分类器和两个聚类模型以实现其目标。首先，通过从草图中提取一组手工设计的特征，分类器将单个笔划识别为描绘边界（形状笔划）或描绘封闭区域（涂鸦笔划）的类型。接着，两个聚类模型将每种类型的笔划解析为不同的组，每组代表目标建筑对象的单个边或面。随后，通过整合形状聚类进行拓扑恢复形成曲线网络，并利用引导环路发现的涂鸦聚类进行曲面重建。我们的评估包含三个方面：通过用户研究确认Strokes2Surface流程在建筑设计用例中的可用性；通过统计分析和在我们收集的数据集上进行消融实验验证特征选择的合理性；并将我们的输出与使用替代方法计算的一系列重建结果进行比较。