The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments
Not on the map. Why?
Abstract (arXiv)
Like sighted people, visually impaired people want to share photographs on social networking services, but find it difficult to identify and select photos from their albums. We aimed to address this problem by incorporating state-of-the-art computer-generated descriptions into Facebook's photo-sharing feature. We interviewed 12 visually impaired participants to understand their photo-sharing experiences and designed a photo description feature for the Facebook mobile application. We evaluated this feature with six participants in a seven-day diary study. We found that participants used the descriptions to recall and organize their photos, but they hesitated to upload photos without a sighted person's input. In addition to basic information about photo content, participants wanted to know more details about salient objects and people, and whether the photos reflected their personal aesthetics. We discuss these findings from the lens of self-disclosure and self-presentation theories and propose new computer vision research directions that will better support visual content sharing by visually impaired people.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 May 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 2; 2025: 0; 2026: 1.
6 papers.
- 2021Computer Vision and Conflicting Values: Describing People with Automated Alt Textcited by 14
- 2023Salient Object Detection for Images Taken by People With Vision Impairmentscited by 7
- 2024EditScribe: Non-Visual Image Editing with Natural Language Verification Loopscited by 6
- 2024A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals' Navigationcited by 5
- 2023Helping Visually Impaired People Take Better Quality Picturescited by 2
- 2026Cripping AI: Reimagining AI Through Lived Disability Experiencescited by 0
- 2026Cripping AI: Reimagining AI Through Lived Disability Experiences3 May 2026
- 2024EditScribe: Non-Visual Image Editing with Natural Language Verification Loops13 Aug 2024
- 2024A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals' Navigation23 Jul 2024
- 2023Helping Visually Impaired People Take Better Quality Pictures14 May 2023
- 2023Salient Object Detection for Images Taken by People With Vision Impairments12 Jan 2023
- 2021Computer Vision and Conflicting Values: Describing People with Automated Alt Text26 May 2021