AI 中文总结
研究在3D物体体积不可改时用电容感应增强其表面的难题，提出生成式计算制造流程，扫描物体获3D网格，生成优化3D传感器设计并展开为2D模板，经切割、附着等步骤实现多点触摸交互，用四种3D几何形状验证了方法。
AI 中文摘要
当3D物体的体积无法修改时，用电容感应增强其表面具有挑战性。本文提出了一种生成式计算制造流程，用于将仅表面的传感器布局改造到3D几何形状上以实现多点触摸交互。该方法扫描真实物体以获取其3D网格，在物理和硬件约束下生成并优化用于互电容感应的驱动线和感应线的3D传感器设计，将设计展开为可从导电材料切割的单个2D模板。制造流程用乙烯基切割机从薄铜箔上切割这些模板，通过将传感器设计投影到动态配准的真实物体上来辅助手动传感器附着。连接所得电极网格到互电容扫描控制器并实时解析触摸交互。用四种3D几何形状展示了该方法并进行了评估。
英文摘要
Augmenting the surface of 3D objects with capacitive sensing is challenging when their volumes cannot be modified. In this paper, we present a generative computational fabrication pipeline that retrofits surface-only sensor layouts to 3D geometries for multi-touch interaction. Our method scans a real-world object to obtain its 3D mesh, generates and optimizes a 3D sensor design of drive and sense lines for mutual-capacitance sensing under physical and hardware constraints, and unfolds the design into individual 2D stencils that can be cut from conductive material. Our fabrication pipeline cuts these stencils from thin copper foil with a vinyl cutter and then assists manual sensor attachment by projecting the sensor design onto the dynamically registered real-world object. We connect the resulting electrode mesh to a mutual-capacitance scanning controller and resolve touch interaction in real time. We demonstrate our approach with four 3D geometries and evaluate our method and fabrication pipeline on them.
CommentsAccepted to ACM SIGGRAPH Conference Papers 2026
Journal refACM SIGGRAPH Conference Papers 2026, Article 145, 2026
