Design and Evaluation of Vision-based Head and Face Tracking Interfaces for Assistive Input

TL;DR

This paper reviews vision-based head and face tracking interfaces for assistive technology, highlighting novel algorithms and evaluation methods to improve human-computer interaction for users with disabilities.

Contribution

It introduces two new facial feature tracking algorithms and presents innovative quantitative and qualitative evaluation techniques for assistive input interfaces.

Findings

Developed two vision-based facial feature tracking algorithms

Proposed new quantitative evaluation tasks

Applied real-world models for qualitative assessment

Abstract

Interaction methods based on computer-vision hold the potential to become the next powerful technology to support breakthroughs in the field of human-computer interaction. Non-invasive vision-based techniques permit unconventional interaction methods to be considered, including use of movements of the face and head for intentional gestural control of computer systems. Facial gesture interfaces open new possibilities for assistive input technologies. This chapter gives an overview of research aimed at developing vision-based head and face-tracking interfaces. This work has important implications for future assistive input devices. To illustrate this concretely we describe work from our own research in which we developed two vision-based facial feature tracking algorithms for human computer interaction and assistive input. Evaluation forms a critical component of this research and we provide examples of new quantitative evaluation tasks as well as the use of model real-world applications for the qualitative evaluation of new interaction styles.