Abstract
3D Sampling is presented as a new method for comprehensive rearrangement and composition of 3D scan data, allowing multi-scale manipulation of surface texturing and subsequent fabrication and re-evaluation using 3D printing. Analogous to sample-based music, 3D Sampling contributes new frameworks, tools, and compositional strategies for the digital remixing, hacking, and appropriating of material qualities, performances, and behaviours directly from physical samples to produce new designs. Case studies are presented which demonstrate 3DJ: a prototype 3D modelling tool for synthesizing haptic and optically performing textures from 3D scan-generated source material, which can be applied in the context of other 3D modelling techniques.
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Acknowledgments
Special thanks to: Skylar Tibbits, Terry Knight, Marc Downie, and Mark Goulthorpe for their mentorship, timely ideas, and guidance, Inés Ariza, for being an excellent colleague, and her generous contribution towards the photographic documentation presented here, Alexander Charidis, for sharing his insights and knowledge of related research efforts in the field of computer graphics, Ben Goldstein, for his help editing and clarifying earlier drafts of this paper, and the MIT-SUTD Collaboration and the MIT Structural Design Lab for supporting the work.
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Patel, S.V., Mueller, C.T. (2015). 3dj: 3d Sampling Haptic and Optically Performative Textures Remixed from 3d Scans. In: Thomsen, M., Tamke, M., Gengnagel, C., Faircloth, B., Scheurer, F. (eds) Modelling Behaviour. Springer, Cham. https://doi.org/10.1007/978-3-319-24208-8_44
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DOI: https://doi.org/10.1007/978-3-319-24208-8_44
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