“Person, Shoes, Tree. Is the Person Naked?” What People with Vision Impairments Want in Image Descriptions
- Abigale Stangl ,
- Meredith Ringel Morris ,
- Danna Gurari
CHI 2020 |
Published by ACM
Access to digital images is important to people who are blind or have low vision (BLV). Many contemporary image description efforts do not take into account this population’s nuanced image description preferences. In this paper, we present a qualitative study that provides insight into 28 BLV people’s experiences with descriptions of digital images from news websites, social networking sites/platforms, eCommerce websites, employment websites, online dating websites/platforms, productivity applications, and e-publications. Our findings reveal how image description preferences vary based on the source where digital images are encountered and the surrounding context. We provide recommendations for the development of next-generation image description technologies inspired by our empirical analysis.
Designing Computer Vision Algorithms to Describe the Visual World to People Who Are Blind or Low Vision
A common goal in computer vision research is to build machines that can replicate the human vision system (for example, detect an object or scene category, describe an object or scene, or locate an object). A natural grand challenge for the artificial intelligence community is to design such technology to assist people who are blind to overcome their real daily visual challenges. In this webinar with Dr. Danna Gurari, Assistant Professor in the School of Information at the University of Texas at Austin, and Dr. Ed Cutrell, Senior Principal Researcher in the Microsoft Research Ability Group, learn how computer vision researchers are working to create vision systems adapted to the needs of those who use them. By creating new dataset challenges, the researchers aim to…