The freeform architectural modeling process often involves two important stages: concept design and digital modeling. In the first stage, architects usually sketch the overall 3D shape and the panel layout on a physical or digital paper briefly. In the second stage, a digital 3D model is created using the sketching as the reference. The digital model needs to incorporate geometric requirements for its components, such as planarity of panels due to consideration of construction costs, which can make the modeling process more challenging. In this work, we present a novel sketch-based system to bridge the concept design and digital modeling of freeform roof-like shapes represented as planar quadrilateral (PQ) meshes. Our system allows the user to sketch the surface boundary and contour lines under axonometric projection and supports the sketching of occluded regions. In addition, the user can sketch feature lines to provide directional guidance to the PQ mesh layout. Given the 2D sketch input, we propose a deep neural network to infer in real-time the underlying surface shape along with a dense conjugate direction field, both of which are used to extract the final PQ mesh. To train and validate our network, we generate a large synthetic dataset that mimics architect sketching of freeform quadrilateral patches. The effectiveness and usability of our system are demonstrated with quantitative and qualitative evaluation as well as user studies.
翻译:自由成型建筑建模过程通常涉及两个重要阶段:概念设计和数字建模。在第一阶段,建筑师通常在物理或数字纸上简短地绘制总体3D形状和面板布局。在第二阶段,以素描为参考,创建了数字3D模型。数字模型需要包含其组成部分的几何要求,例如板块在考虑建筑成本时的平面设计,这样可以使建模过程更具挑战性。在这项工作中,我们提出了一个新的基于素描的系统,以连接以规划四边形(PQ)为代表的自由成型屋顶形状的概念设计和数字建模。我们的系统允许用户在xonotologic 投影下绘制表面边界和轮廓线图,并支持绘制覆盖区域图谱图。此外,用户可以绘制地谱线,为PQ网布局提供方向指导。根据2D的素描输入,我们建议建立一个深神经网络,以实时推导基础表表面形状,与一个密成型的圆形圆形四边形方向场(PQ)的外观,用来提取我们最终的成型系统。