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Images, Words, and Imagination: Accessible Descriptions to Support Blind and Low Vision Art Exploration and Engagement.
Doore, Stacy A; Istrati, David; Xu, Chenchang; Qiu, Yixuan; Sarrazin, Anais; Giudice, Nicholas A.
Afiliación
  • Doore SA; INSITE Lab, Department of Computer Science, Colby College, Waterville, ME 04901, USA.
  • Istrati D; INSITE Lab, Department of Computer Science, Colby College, Waterville, ME 04901, USA.
  • Xu C; Department of Computer Science, Fu Foundation School of Engineering and Applied Science, Columbia University, New York, NY 10027, USA.
  • Qiu Y; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA.
  • Sarrazin A; Sonos, San Francisco, CA 94109, USA.
  • Giudice NA; VEMI Lab, School of Computing and Information Science, University of Maine, Orono, ME 04469, USA.
J Imaging ; 10(1)2024 Jan 18.
Article en En | MEDLINE | ID: mdl-38249011
ABSTRACT
The lack of accessible information conveyed by descriptions of art images presents significant barriers for people with blindness and low vision (BLV) to engage with visual artwork. Most museums are not able to easily provide accessible image descriptions for BLV visitors to build a mental representation of artwork due to vastness of collections, limitations of curator training, and current measures for what constitutes effective automated captions. This paper reports on the results of two studies investigating the types of information that should be included to provide high-quality accessible artwork descriptions based on input from BLV description evaluators. We report on (1) a qualitative study asking BLV participants for their preferences for layered description characteristics; and (2) an evaluation of several current models for image captioning as applied to an artwork image dataset. We then provide recommendations for researchers working on accessible image captioning and museum engagement applications through a focus on spatial information access strategies.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: J Imaging Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: J Imaging Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos
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