Deformation capture via soft and stretchable sensor arrays

Oliver Glauser, Daniele Panozzo, Otmar Hilliges, Olga Sorkine-Hornung

Research output: Contribution to journalArticlepeer-review

Abstract

We propose a hardware and software pipeline to fabricate flexible wearable sensors and use them to capture deformations without line-of-sight. Our first contribution is a low-cost fabrication pipeline to embed multiple aligned conductive layers with complex geometries into silicone compounds. Overlapping conductive areas from separate layers form local capacitors that measure dense area changes. Contrary to existing fabrication methods, the proposed technique only requires hardware that is readily available in modern fablabs. While area measurements alone are not enough to reconstruct the full 3D deformation of a surface, they become sufficient when paired with a data-driven prior. A novel semi-automatic tracking algorithm, based on an elastic surface geometry deformation, allows us to capture ground-truth data with an optical mocap system, even under heavy occlusions or partially unobservable markers. The resulting dataset is used to train a regressor based on deep neural networks, directly mapping the area readings to global positions of surface vertices. We demonstrate the flexibility and accuracy of the proposed hardware and software in a series of controlled experiments and design a prototype of wearable wrist, elbow, and biceps sensors, which do not require line-of-sight and can be worn below regular clothing.

Original languageEnglish (US)
Article number16
JournalACM Transactions on Graphics
Volume38
Issue number2
DOIs
StatePublished - Apr 2019

Keywords

  • Capacitive
  • Deformation capture
  • Sensor array
  • Stretchable

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

Fingerprint Dive into the research topics of 'Deformation capture via soft and stretchable sensor arrays'. Together they form a unique fingerprint.

Cite this