Robust Eye-Based Dwell-Free Typing

ABSTRACT

For a subset of physically challenged people, assistive technologies, such as alternative form of text entry, can be of tremendous benefit. However, speed of text entry with current methods limits their more widespread adoption. Eye gaze technologies have potential for text entry, but still tend to be relatively slow. Recently dwell-free eye-typing systems have been proposed, but can be vulnerable to common text entry problems, such as selection of the wrong letters. In this article, a recognition approach for inferring the words which the user intends to type is proposed. The method is robust to missing letters and even when a neighboring letter on the keyboard is incorrectly selected. Simulation and experiment results suggest that our proposed approach has better accuracy and more resilience to common text entry errors than other currently proposed dwell-free systems.

Notes

¹ http://theeyetribe.com/.

² http://www.swype.com/.

³ http://swiftkey.com/en/.

Additional information

Notes on contributors

Yi Liu

Yi Liu is a PhD student of computer science at Interdisciplinary Graduate School, Nanyang Technological University. His research spans brain–computer interaction, human–computer interaction, eye tracking, and computer vision. He obtained his BEng from the School of Software, Harbin Institute of Technology, China.

Bu-Sung Lee

Bu-Sung Lee is currently an Associate Professor with the School of Computer Science and Engineering, Nanyang Technological University. He held a joint position as Director (Research) HP Labs, Singapore, from 2010 till 2012. His major research interests are in the area of mobile and pervasive network, distributed systems, and cloud/grid computing technology.

Martin J. McKeown

Martin J. McKeown is a Professor of Medicine and ECE (Adjunct), Director of the Pacific Parkinson’s Research Centre at UBC, and holds the PPRI/UBC Chair in Parkinson’s Research. In addition to seeing patients with Movement Disorders, he is developing new analytical methods to assess brain imaging data and investigating novel treatments for Parkinson’s Disease.