Selection strategies in gaze interaction

This thesis deals with selection strategies in gaze interaction, specifically for a context where gaze is the sole input modality for users with severe motor impairments. The goal has been to contribute to the subfield of assistive technology where gaze interaction is necessary for the user to achieve autonomous communication and environmental control. From a theoretical point of view research has been done on the physiology of the gaze, eye tracking technology, and a taxonomy of existing selection strategies has been developed. Empirically two overall approaches have been taken. Firstly, end-user research has been conducted through interviews and observation. The capabilities, requirements, and wants of the end-user have been explored. Secondly, several applications have been developed to explore the selection strategy of single stroke gaze gestures (SSGG) and aspects of complex gaze gestures. The main finding is that single stroke gaze gestures can successfully be used as a selection strategy. Some of the features of SSGG are: That horizontal single stroke gaze gestures are faster than vertical single stroke gaze gestures; That there is a significant difference in completion time depending on gesture length; That single stroke gaze gestures can be completed without visual feedback; That gaze tracking equipment has a significant effect on the completion times and error rates of single stroke gaze gestures; That there is not a significantly greater chance of making selection errors with single stroke gaze gestures compared with dwell selection. The overall conclusion is that the future of gaze interaction should focus on developing multi-modal interactions for mono-modal input

SymbolDesign: A User-centered Method to Design Pen-based Interfaces and Extend the Functionality of Pointer Input Devices

A method called "SymbolDesign" is proposed that can be used to design user-centered interfaces for pen-based input devices. It can also extend the functionality of pointer input devices such as the traditional computer mouse or the Camera Mouse, a camera-based computer interface. Users can create their own interfaces by choosing single-stroke movement patterns that are convenient to draw with the selected input device and by mapping them to a desired set of commands. A pattern could be the trace of a moving finger detected with the Camera Mouse or a symbol drawn with an optical pen. The core of the SymbolDesign system is a dynamically created classifier, in the current implementation an artificial neural network. The architecture of the neural network automatically adjusts according to the complexity of the classification task. In experiments, subjects used the SymbolDesign method to design and test the interfaces they created, for example, to browse the web. The experiments demonstrated good recognition accuracy and responsiveness of the user interfaces. The method provided an easily-designed and easily-used computer input mechanism for people without physical limitations, and, with some modifications, has the potential to become a computer access tool for people with severe paralysis.National Science Foundation (IIS-0093367, IIS-0308213, IIS-0329009, EIA-0202067

Presenting in Virtual Worlds: Towards an Architecture for a 3D Presenter explaining 2D-Presented Information

Entertainment, education and training are changing because of multi-party interaction technology. In the past we have seen the introduction of embodied agents and robots that take the role of a museum guide, a news presenter, a teacher, a receptionist, or someone who is trying to sell you insurances, houses or tickets. In all these cases the embodied agent needs to explain and describe. In this paper we contribute the design of a 3D virtual presenter that uses different output channels to present and explain. Speech and animation (posture, pointing and involuntary movements) are among these channels. The behavior is scripted and synchronized with the display of a 2D presentation with associated text and regions that can be pointed at (sheets, drawings, and paintings). In this paper the emphasis is on the interaction between 3D presenter and the 2D presentation

Presenting in Virtual Worlds: An Architecture for a 3D Anthropomorphic Presenter

Multiparty-interaction technology is changing entertainment, education, and training. Deployed examples of such technology include embodied agents and robots that act as a museum guide, a news presenter, a teacher, a receptionist, or someone trying to sell you insurance, homes, or tickets. In all these cases, the embodied agent needs to explain and describe. This article describes the design of a 3D virtual presenter that uses different output channels (including speech and animation of posture, pointing, and involuntary movements) to present and explain. The behavior is scripted and synchronized with a 2D display containing associated text and regions (slides, drawings, and paintings) at which the presenter can point. This article is part of a special issue on interactive entertainment

Analyzing Nonverbal Listener Responses using Parallel Recordings of Multiple Listeners

In this paper we study nonverbal listener responses on a corpus with multiple parallel recorded listeners. These listeners were meant to believe that they were the sole listener, while in fact there were three persons listening to the same speaker. The speaker could only see one of the listeners. We analyze the impact of the particular setup of the corpus on the behavior and perception of the two types of listeners; the listeners that could be seen by the speaker and the listeners that could not be seen. Furthermore we compare the nonverbal listening behaviors of these three listeners to each other with regard to timing and form. We correlate these behaviors with behaviors of the speaker, like pauses and whether the speaker is looking at the listeners or not

Human-Robot Interaction Based on Gaze Gestures for the Drone Teleoperation

Teleoperation has been widely used to perform tasks in dangerous and unreachable environments by replacing humans with controlled agents. The idea of human-robot interaction (HRI) is very important in teleoperation. Conventional HRI input devices include keyboard, mouse and joystick, etc. However, they are not suitable for handicapped users or people with disabilities. These devices also increase the mental workload of normal users due to simultaneous operation of multiple HRI input devices by hand. Hence, HRI based on gaze tracking with an eye tracker is presented in this study. The selection of objects is of great importance and occurs at a high frequency during HRI control. This paper introduces gaze gestures as an object selection strategy into HRI for drone teleoperation. In order to test and validate the performance of gaze gestures selection strategy, we evaluate objective and subjective measurements, respectively. Drone control performance, including mean task completion time and mean error rate, are the objective measurements. The subjective measurement is the analysis of participant perception. The results showed gaze gestures selection strategy has a great potential as an additional HRI for use in agent teleoperation