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Sketch2PQ: Freeform Planar Quadrilateral Mesh Design via a Single Sketch. | LitMetric

AI Article Synopsis

  • The architectural modeling process consists of two main stages: concept design, where architects create 3D sketches, and digital modeling, where those sketches are transformed into detailed digital 3D models.
  • A novel sketch-based system is introduced, facilitating the transition from concept design to digital modeling of freeform roof shapes through user-friendly sketching tools that support features like occluded regions and directional lines.
  • To implement this system, a deep neural network analyzes 2D sketches in real-time to derive the surface shape and structure, validated through a comprehensive synthetic dataset and user evaluations highlighting its effectiveness and usability.

Article Abstract

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 sketch as a reference. The digital model needs to incorporate geometric requirements for its components, such as the 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.

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Source
http://dx.doi.org/10.1109/TVCG.2022.3170853DOI Listing

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