Skip to main navigation Skip to search Skip to main content
9   Link opens in a new tab Citations (SciVal)

Abstract

We introduce Pic2Tac, a novel system that automatically converts photographs into tactile images. It offers an alternative way to communicate visual information that is difficult to express using braille or alternative text. Current methods for creating tactile images are either limited in representation, or require handmade artefacts. Pic2Tac employs a unique approach that avoids a literal representation of image content (e.g. contours). Instead, it detects salient semantic content within photographs and translates them into tactile images using dedicated ‘tactile words’. Foreground objects are represented using icons, and patterns are used for background regions. The resulting binary image is printed on swell paper, where black regions rise to form a tactile image. Studies involving 60 participants, both sighted and with visual impairments, demonstrate the effectiveness of these tactile images in communicating semantic meaning. Our findings show that tactile and visual descriptions of scenes matched significantly. Overall, Pic2Tac is an affordable way to create accessible tactile images, costing only 1.50 USD per sheet.
Original languageEnglish
DOIs
Publication statusPublished - 11 Feb 2024
Event
TEI '24: Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction
- Cork, Ireland
Duration: 11 Feb 202414 Feb 2024

Conference

Conference
TEI '24: Eighteenth International Conference on Tangible, Embedded, and Embodied Interaction
Country/TerritoryIreland
CityCork
Period11/02/2414/02/24

Funding

We extend our sincere thanks to all participants who volunteered for our study. Their cooperation and insightful comments were instrumental in making this paper possible. Special thanks to Sarah Pool (Specialist Support Professional for Deaf students), for her language editing expertise, and to Luiza Bell (Assistive Technologist), for her help in writing descriptions to ensure the accessibility of figures for screen readers. We are grateful to our anonymous reviewers for their valuable suggestions. Heartfelt gratitude is extended to the contributors of ADE20K Dataset, Creative Fabrica, Flaticon, Flickr, Iconfinder, Icon Library, Needpix, Pixabay, Public Domain Pictures, The Noun Project, and Wikipedia. Their contributions, both as training data for our ML models and in enriching the visual content of this paper, have been invaluable. This research received support and partial funding from the UKRI EPSRC Centre for Doctoral Training in Digital Entertainment (CDE), EP/L016540/1, and the UKRI Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA 2.0), EP/T022523/1. The study design, data collection and analysis, decision to publish, and manuscript preparation were independent of the funders.

FundersFunder number
Engineering and Physical Sciences Research CouncilEP/L016540/1
UK Research & InnovationEP/T022523/1

Keywords

  • Accessibility
  • Photographs
  • Semantic information
  • Tactile images

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Pic2Tac: Creating Accessible Tactile Images using Semantic Information from Photographs'. Together they form a unique fingerprint.

Cite this