The Suitability of Texture Vibrations Based on Visually Perceived Virtual Textures in Bimodal and Trimodal Conditions

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung


In this study, suitability of recorded and simplified texture vibrations are evaluated according to visual textures displayed on a screen. The tested vibrations are 1) recorded vibration, 2) single sinusoids, and 3) band-limited white noise which were used in the previous work. In the former study, suitability of texture vibrations were evaluated according to real textures by touching. Nevertheless, texture vibrations should be also tested based on texture images considering the fact that users interact with only virtual (visual) objects on touch devices. Thus, the aim of this study is to assess the congruence between the vibrotactile feedback and the texture images with the absence and the presence of auditory feedback. Two types of auditory feedback were used for the trimodal test, and they were tested in different loudness levels. Therefore, the most plausible combination of vibrotactile and audio stimuli when exploring the visual textures can be determined. Based on the psychophysical tests, the similarity ratings of the texture vibrations were not concluded significantly different from each other in bimodal condition as opposed to the former study. In the trimodal judgments, synthesized sound influenced the similarity ratings significantly while touch sound did not affect the perceived similarity.


Titel2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)
Herausgeber (Verlag)Wiley-IEEE Press
ISBN (Print)978-1-7281-9323-6
PublikationsstatusVeröffentlicht - 24 Sept. 2020


Titel2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)
Dauer21 - 24 September 2020
OrtTampere, Finland

Externe IDs

Scopus 85099195052
ORCID /0000-0001-5346-6021/work/142254532
ORCID /0000-0002-0803-8818/work/142257054



  • Vibrations, Visualization, Conferences, White noise, Signal processing