We are investigating the use of eye-tracking as a user-interface to govern the placement of Augmented Reality labels. We compared four gaze-based algorithms to a naive approach. Using a simple information retrieval task, we tested approaches on a typical LCD and subsequently on a tablet device. One particular method worked well in terms of speed and accuracy. The naive method also worked well, with eye-tracking visual clutter is dramatically decreased.
In this work, we explore brain computer interfaces (BCI) as a means to securely access consumer electronics for daily interaction. A variety of wireless consumer-level BCI headsets are compared and analyzed via a common open source toolbox. Experiments are then designed to test their
real-time biosignal processing capabilities. Finally, the capacity for brain signals to serve as passwords in common consumer electronics is demonstrated via these relatively simple devices.