Some individuals have difficulty using standard hand-manipulated input devices such as a mouse and a keyboard effectively. For such users who at the same time have sufficient control over face and head movement, a robust perceptual or vision-based user interface that can track face movement can significantly help them. Using vision-based consumer devices makes such a user interface readily available and allows its use to be non-intrusive. Designing this type of user interface presents some significant challenges particularly with accuracy and usability. This research investigates such problems and proposes solutions to create a usable and robust face tracking user interface using currently available state-of-the-art technology. In particular, the input control in such an interface is divided into its logical components and studied one by one, namely, user input, capture technology, feature retrieval, feature processing, and pointer behavior. Different options for these components are studied and evaluated to see if they contribute to more efficient use of the interface. The evaluation is done using standard tests created for this purpose. The tests were done by a single user. The results can serve as a precursor to a full-scale usability study, various improvements, and eventual deployment for actual use. The primary contributions of this research include a logical organization and evaluation of the input process and its different components in face tracking user interfaces, a common library for computer control that can be used by various face tracking engines, an adaptive pointing input style that makes pointing using natural movement easier, and a test suite that can be used to measure performance of various user interfaces for desktop systems.
College and Department
Ira A. Fulton College of Engineering and Technology; Technology
BYU ScholarsArchive Citation
Villaroman, Norman, "Face Tracking User Interfaces Using Vision-Based Consumer Devices" (2013). All Theses and Dissertations. 3941.
face, detection, tracking, filters, accessibility, assistive technology, depth, perceptual user interface, interface design, HCI, consumer devices, computer input, computer vision, Kinect