Learning to Feel Textures: Predicting Perceptual Similarities From Unconstrained Finger-Surface Interactions-Reference-Cited by-同舟云学术

Learning to Feel Textures: Predicting Perceptual Similarities From Unconstrained Finger-Surface Interactions

Published:2022-10-01 Issue:4 Volume:15 Page:705-717
ISSN:1939-1412
Container-title:IEEE Transactions on Haptics
language:
Short-container-title:IEEE Trans. Haptics

Author:

Richardson Benjamin A.¹^ORCID,Vardar Yasemin²^ORCID,Wallraven Christian³^ORCID,Kuchenbecker Katherine J.⁴^ORCID

Affiliation:

1. Haptic Intelligence Department at the Max Planck Institute for Intelligent Systems and with the Computer Science Department, University of Stuttgart, Stuttgart, Germany

2. Department of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands

3. Departments of Artificial Intelligence and Brain and Cognitive Engineering, Korea University, Seoul, South Korea

4. Haptic Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany

Funder

Institute for Information and Communications Technology Promotion

Korea Government

National Research Foundation of Korea

German Ministry of Education and Research

Tübingen AI Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Human-Computer Interaction

Link

http://xplorestaging.ieee.org/ielx7/4543165/9991904/09913733.pdf?arnumber=9913733

Reference46 articles.

1. Learning to see stuff;storrs;Current Opinion in Behavioral Sciences,2019

2. Haptic and visual perception of roughness

3. Softness Discrimination With a Tool

4. Dimensional Reduction of High-Frequency Accelerations for Haptic Rendering

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