<!–Date/Time: 1-2pm October 27th, 2011
Location: 1.33a Jack Cole, University of St Andrews (directions)
Second Talk:
Speaker: David Flatla, Interaction Lab, University of Saskatchewan, Canada–>
Title: Using Situation-Specific Models of Colour Differentiation to Assist Individuals with Colour Vision Deficiency
Abstract:
Approximately 10% of the world’s population experiences either congenital, acquired, or situationally-induced colour vision deficiency (CVD – commonly called colour blindness). People with CVD often confuse colours that those without CVD can distinguish. When working in digital environments, CVD can lead to problems ranging from minor nuisances (e.g., being unable to distinguish ‘visited’ from ‘not visited’ links on a webpage) to major safety concerns (e.g., not seeing colour-coded warning messages).
Recently, recolouring tools have been developed that modify the colours presented on a display to eliminate the colour confusion that people with CVD experience. However, these tools are limited to individuals with dichromatic CVD – a particularly severe and somewhat rare form of congenital CVD. As a result, individuals with acquired and situationally-induced CVD as well as those with non-dichromatic forms of congenital CVD continue to have difficulties.
In this talk, I will present my PhD research toward a new recolouring tool based on situation-specific models of colour differentiation. I will first present my work on situation-specific models that capture the colour differentiation abilities of any individual in any environment through a two-minute in-situ calibration procedure. I will then discuss my most recent work on developing a recolouring tool based on situation-specific models of colour differentiation.
About David:
David Flatla is a PhD student at the University of Saskatchewan in Canada under the supervision of Dr. Carl Gutwin. His research focusses on the field of accessibility, particularly on how to help individuals with colour vision deficiency (CVD – commonly called colour blindness). To do this, he invented situation-specific models of colour differentiation that utilize in-situ calibration to accurately capture how people differentiate colors. He publishes at conferences like CHI and ASSETS. At UIST this year, he presented research exploring how to make boring calibrations fun by turning them into games.