FrictGAN : Frictional Signal Generation from Fabric Texture Images using Generative Adversarial Network

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationICAT-EGVE 2020
Subtitle of host publicationInternational Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments
PublisherThe Eurographics Association
Pages11-15
Number of pages5
ISBN (Print)978-3-03868-111-3
Publication statusPublished - Dec 2020

Conference

TitleICAT-EGVE2020
LocationVirtual
City
Period2 - 4 December 2020

Abstract

The electrostatic tactile display could render the tactile feeling of different haptic texture surfaces by generating the frictional force through voltage modulation when a finger is sliding on the display surface. However, it is challenging to prepare and fine-tune the appropriate frictional signals for haptic design and texture simulation. We present FrictGAN, a deep-learningbased framework to synthesize frictional signals for electrostatic tactile displays from fabric texture images. Leveraging GANs (Generative Adversarial Networks), FrictGAN could generate the displacement-series data of frictional coefficients for the electrostatic tactile display to simulate the tactile feedback of fabric material. Our preliminary experimental results showed that FrictGAN could achieve considerable performance on frictional signal generation based on the input images of fabric textures.

Research Area(s)

  • Generative adversarial network (GAN), Virtual Reality

Citation Format(s)

FrictGAN : Frictional Signal Generation from Fabric Texture Images using Generative Adversarial Network. / Cai, Shaoyu; Ban, Yuki; Narumi, Takuji; Zhu, Kening.

ICAT-EGVE 2020: International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments. The Eurographics Association, 2020. p. 11-15.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review