Proximity3D: Shape from Capacitive Proximity on Sensing Manifold

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On September 7, 2026, arXiv cs.CV published the paper “Proximity3D: Shape from Capacitive Proximity on Sensing Manifold”, which proposes a three-dimensional shape reconstruction method based on capacitive proximity sensing. This study maps the physical distance between objects and sensors into feature representations on the sensing manifold. By modeling the nonlinear relationship of capacitive signals with distance, it is possible to recover the three-dimensional geometric structure of objects from single-dimensional proximity measurement data. This method aims to overcome the limitations of traditional depth estimation, which rely on active illumination or stereo vision. By utilizing passive capacitive sensing in low-cost and low-power scenarios, it provides a new approach for contactless 3D sensing.

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A arXiv cs.CV en 2026-09-07 12:00

本文提出 Proximity3D 方法，利用弯曲电容织物作为非平面传感流形进行形状重建。该方法将每次扫描表示为该流形上的电容邻近场，并引入多视图前馈重建模型聚合已知传感器视角下的这些场以恢复物体形状。模拟与物理实验表明，该方法能鲁棒地从弯曲传感表面获取的电容邻近信号中重建形状，为通过具身传感实现机器人近场几何感知开辟了新途径。