EasySnap: real-time audio feedback for blind photography

Authors:
Samuel White;Hanjie Ji;Jeffrey P. Bigham
Affiliations:
University of Rochester, Rochester, NY, USA;University of Rochester, Rochester, NY, USA;University of Rochester, Rochester, NY, USA
Venue:
UIST '10 Adjunct proceedings of the 23nd annual ACM symposium on User interface software and technology
Year:
2010

Citing 3
Cited 7

Speeded-Up Robust Features (SURF)

Computer Vision and Image Understanding
Low cost blur image detection and estimation for mobile devices

ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
VizWiz: nearly real-time answers to visual questions

UIST '10 Proceedings of the 23nd annual ACM symposium on User interface software and technology

Using real-time feedback to improve visual question answering

CHI '12 Extended Abstracts on Human Factors in Computing Systems
SmartDCap: semi-automatic capture of higher quality document images from a smartphone

Proceedings of the 2013 international conference on Intelligent user interfaces
Access lens: a gesture-based screen reader for real-world documents

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Accessible photo album: enhancing the photo sharing experience for people with visual impairment

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A qualitative study to support a blind photography mobile application

Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
Real time object scanning using a mobile phone and cloud-based visual search engine

Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility
Answering visual questions with conversational crowd assistants

Proceedings of the 15th International ACM SIGACCESS Conference on Computers and Accessibility

Quantified Score

Hi-index	0.00

Visualization

Abstract

This demonstration presents EasySnap, an application that enables blind and low-vision users to take high-quality photos by providing real-time audio feedback as they point their existing camera phones. Users can readily follow the audio instructions to adjust their framing, zoom level and subject lighting appropriately. Real-time feedback is achieved on current hardware using computer vision in conjunction with use patterns drawn from current blind photographers.