Details

Autor(en) / Beteiligte

• Geddes, Connor
• Flatla, David R.
• Tigwell, Garreth W.
• Peiris, Roshan L
• Barbosa, Simone
• Appert, Caroline
• Lampe, Cliff
• Shamma, David A.
• Yatani, Koji
• Drucker, Steven
• Williamson, Julie

Titel

Improving Colour Patterns to Assist People with Colour Vision Deficiency

Ist Teil von

• Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, 2022, p.1-17

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2022

Link zum Volltext

Quelle

ACM Digital Library Complete

Beschreibungen/Notizen

• Many daily tasks rely on accurately identifying and distinguishing between different colours. However, these tasks can be frustrating and potentially dangerous for people with Colour Vision Deficiency (CVD). Despite prior work exploring how pattern overlays on top of colours can support people with CVD, the solutions were often unintuitive or required significant training to become proficient. We address this problem by creating two new colour patterns (ColourIconizer, ColourMix). We evaluated these patterns against a previously published colour pattern (ColourMeters) using an online evaluation with three new colour identification tasks (Selection Task, Transition Task, Sorting Task). ColourMeters helped with the Transition Task, but struggled with the Selection and Sorting Tasks. Conversely, ColourIconizer helped with the Selection and Sorting Tasks but struggled to help on the Transition Task. ColourMix provided general assistance on all tasks. Our combined results help inform and improve the design of future colour patterns.