Noise Challenges in Monomodal Gaze Interaction

Modern graphical user interfaces (GUIs) are designed with able-bodied users in mind. Operating these interfaces can be impossible for some users who are unable to control the conventional mouse and keyboard. An eye tracking system offers possibilities for independent use and improved quality of life via dedicated interface tools especially tailored to the users ’ needs (e.g., interaction, communication, e-mailing, web browsing and entertainment). Much effort has been put towards robustness, accuracy and precision of modern eyetracking systems and there are many available on the market. Even though gaze tracking technologies have undergone dramatic improvements over the past years, the systems are still very imprecise. This thesis deals with current challenges of mono-modal gaze interaction and aims at improving access to technology and interface control for users who are limited to the eyes only. Low-cost equipment in eye tracking contributes toward improved affordability but potentially at the cost of introducing more noise in the system due to the lower quality of hardware. This implies that methods of dealing with noise and creative approaches towards getting the best out of the data stream are most wanted. The work in this thesis presents three contributions that may advance the use of low-cost mono-modal gaze tracking and research in the field:- An assessment of a low-cost open-source gaze tracker and two eye tracking systems through an accuracy and precision test and a performance evaluation.- Development and evaluation of a novel innovative 3D typing system with high tolerance to noise that is based on continuous panning and zooming.- Development and evaluation of novel selection tools that compensate for noisy input during small-target selections in modern GUIs. This thesis may be of particular interest for those working on the use of eye trackers for gaze interaction and how to deal with reduced data quality. The work in this thesis is accompanied by several software applications developed for the research projects that can be freely downloaded from the eyeInteract appstore 1

Can Gaze Beat Touch? A Fitts' Law Evaluation of Gaze, Touch, and Mouse Inputs

Gaze input has been a promising substitute for mouse input for point and select interactions. Individuals with severe motor and speech disabilities primarily rely on gaze input for communication. Gaze input also serves as a hands-free input modality in the scenarios of situationally-induced impairments and disabilities (SIIDs). Hence, the performance of gaze input has often been compared to mouse input through standardized performance evaluation procedure like the Fitts' Law. With the proliferation of touch-enabled devices such as smartphones, tablet PCs, or any computing device with a touch surface, it is also important to compare the performance of gaze input to touch input. In this study, we conducted ISO 9241-9 Fitts' Law evaluation to compare the performance of multimodal gaze and foot-based input to touch input in a standard desktop environment, while using mouse input as the baseline. From a study involving 12 participants, we found that the gaze input has the lowest throughput (2.55 bits/s), and the highest movement time (1.04 s) of the three inputs. In addition, though touch input involves maximum physical movements, it achieved the highest throughput (6.67 bits/s), the least movement time (0.5 s), and was the most preferred input. While there are similarities in how quickly pointing can be moved from source to target location when using both gaze and touch inputs, target selection consumes maximum time with gaze input. Hence, with a throughput that is over 160% higher than gaze, touch proves to be a superior input modality

A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms

In this paper a review is presented of the research on eye gaze estimation techniques and applications, that has progressed in diverse ways over the past two decades. Several generic eye gaze use-cases are identified: desktop, TV, head-mounted, automotive and handheld devices. Analysis of the literature leads to the identification of several platform specific factors that influence gaze tracking accuracy. A key outcome from this review is the realization of a need to develop standardized methodologies for performance evaluation of gaze tracking systems and achieve consistency in their specification and comparative evaluation. To address this need, the concept of a methodological framework for practical evaluation of different gaze tracking systems is proposed.Comment: 25 pages, 13 figures, Accepted for publication in IEEE Access in July 201

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

Speed and Accuracy of Gaze Gestures

We conducted an experiment where participants carried out six gaze gesture tasks. The gaze paths were analyzed to find out the speed and accuracy of the gaze gestures. As a result, the gaze gestures took more time than we anticipated and only the very fastest participants got close to what was expected. There was not much difference in performance times between small and large gaze gestures, because the participants reached significantly faster speed when making large gestures than small gestures. Curved shapes were found difficult to follow and time-consuming when followed properly. In general, the accuracy in following shapes was sometimes very poor. We believe that to improve the speed and accuracy of gaze gestures, proper feedback must be used more than in our experiment