Generative design of decorative architectural parts
This paper presents a method for generative design of decorative architectural parts such as corbel, moulding and panel, which usually have clear structure and aesthetic details. The method is composed of two components: offline learning and online generation. The offline learning trains a 2D CurveI...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/159966 |
| _version_ | 1811686567012466688 |
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| author | Zhang, Yuzhe Ong, Chan Chi Zheng, Jianmin Lie, Seng Tjhen Guo, Zhendong |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Zhang, Yuzhe Ong, Chan Chi Zheng, Jianmin Lie, Seng Tjhen Guo, Zhendong |
| author_sort | Zhang, Yuzhe |
| collection | NTU |
| description | This paper presents a method for generative design of decorative architectural parts such as corbel, moulding and panel, which usually have clear structure and aesthetic details. The method is composed of two components: offline learning and online generation. The offline learning trains a 2D CurveInfoGAN and a 3D VoxelVAE that learn the feature representations of the parts in a dataset. The online generation proceeds with an evolution procedure that evolves to product new generation of part components by selecting, crossing over and mutating features, followed by a feature-driven deformation that synthesizes the 3D mesh representation of new models. Built upon these technical components, a generative design tool is developed, which allows the user to input a decorative architectural model as a reference and then generates a set of new models that are “more of the same” as the reference and meanwhile exhibit some “surprising” elements. The experiments demonstrate the effectiveness of the method and also showcase the use of classic geometric modelling and advanced machine learning techniques in modelling of architectural parts. |
| first_indexed | 2024-10-01T05:02:28Z |
| format | Journal Article |
| id | ntu-10356/159966 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:02:28Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1599662022-07-06T06:47:34Z Generative design of decorative architectural parts Zhang, Yuzhe Ong, Chan Chi Zheng, Jianmin Lie, Seng Tjhen Guo, Zhendong School of Civil and Environmental Engineering School of Computer Science and Engineering Engineering::Civil engineering Decorative Architectural Parts Generative Design This paper presents a method for generative design of decorative architectural parts such as corbel, moulding and panel, which usually have clear structure and aesthetic details. The method is composed of two components: offline learning and online generation. The offline learning trains a 2D CurveInfoGAN and a 3D VoxelVAE that learn the feature representations of the parts in a dataset. The online generation proceeds with an evolution procedure that evolves to product new generation of part components by selecting, crossing over and mutating features, followed by a feature-driven deformation that synthesizes the 3D mesh representation of new models. Built upon these technical components, a generative design tool is developed, which allows the user to input a decorative architectural model as a reference and then generates a set of new models that are “more of the same” as the reference and meanwhile exhibit some “surprising” elements. The experiments demonstrate the effectiveness of the method and also showcase the use of classic geometric modelling and advanced machine learning techniques in modelling of architectural parts. Ministry of Education (MOE) This work is supported by the Ministry of Education, Singapore, under its MoE Tier-2 Grant (2017-T2-1-076). 2022-07-06T06:28:55Z 2022-07-06T06:28:55Z 2022 Journal Article Zhang, Y., Ong, C. C., Zheng, J., Lie, S. T. & Guo, Z. (2022). Generative design of decorative architectural parts. Visual Computer, 38(4), 1209-1225. https://dx.doi.org/10.1007/s00371-021-02142-1 0178-2789 https://hdl.handle.net/10356/159966 10.1007/s00371-021-02142-1 2-s2.0-85106276402 4 38 1209 1225 en 2017-T2-1-076 Visual Computer © 2021 The Authors, under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved. |
| spellingShingle | Engineering::Civil engineering Decorative Architectural Parts Generative Design Zhang, Yuzhe Ong, Chan Chi Zheng, Jianmin Lie, Seng Tjhen Guo, Zhendong Generative design of decorative architectural parts |
| title | Generative design of decorative architectural parts |
| title_full | Generative design of decorative architectural parts |
| title_fullStr | Generative design of decorative architectural parts |
| title_full_unstemmed | Generative design of decorative architectural parts |
| title_short | Generative design of decorative architectural parts |
| title_sort | generative design of decorative architectural parts |
| topic | Engineering::Civil engineering Decorative Architectural Parts Generative Design |
| url | https://hdl.handle.net/10356/159966 |
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