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Sketch2PQ: freeform planar quadrilateral mesh design via a single sketch

Deng, Zhi, Liu, Yang, Pan, Hao, Jabi, Wassim, Zhang, Juyong and Deng, Bailin 2022. Sketch2PQ: freeform planar quadrilateral mesh design via a single sketch. IEEE Transactions on Visualization and Computer Graphics 10.1109/TVCG.2022.3170853

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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.

Item Type: Article
Status: In Press
Schools: Architecture
Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 1077-2626
Date of First Compliant Deposit: 25 April 2022
Date of Acceptance: 24 April 2022
Last Modified: 12 May 2022 03:09
URI: https://orca.cardiff.ac.uk/id/eprint/149335

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