Eye tracking in translation process research: methodological challenges and solutions

Eye tracking has been eagerly adopted as a technique in translation process research in recent years and, with it, comes a long list of methodological challenges, some of which are specific to translation process research, some of which are more general. This paper represents an attempt by a recent convert to eye tracking to document the various challenges and to offer suggestions for how some of them might be addressed by others who are interested in embracing this very interesting mode of investigation. It is difficult to comment only on those challenges related to eye tracking without mentioning issues that pertain to the more general questions of research design in the domain of translation process research as the two are inevitably linked. By highlighting challenges, one is inevitably exposing research design weaknesses. However, this should not be viewed negatively but should rather be seen as a means of improving the quality of combined research outputs with the aim of maturing the domain. This paper is broadly divided into two parts: the first discusses the methodological challenges, which in turn are divided into the categories of research environment, research participants, ethics, data explosion and validity. Each section is then repeated in the second part of the paper, which offers suggestions on how the challenges might be addressed

A blueprint for integrated eye-controlled environments

Eye-based environmental control requires innovative solutions for supporting effective user interaction, for allowing home automation and control, and for making homes more "attentive" to user needs. Several approaches have already been proposed, which can be seen as isolated attempts to address only partial issues and specific sub-sets of the general problem. This paper aims at tackling gaze-based home automation as a whole, exploiting state of the art technologies and trying to integrate interaction modalities than are currently supported and that may supported in a near future. User-home interaction is sought through two, complementary, interaction patterns: direct interaction and mediated interaction. Integration between home appliances/devices and user interfaces is granted by a central point of abstraction/harmonization called House Manager. Innovative points can be identified in the wide flexibility of the approach which allows on one side to integrate virtually all home devices having a communication interface, and, on the other side, mixes-up direct and mediated user interaction exploiting the advantages of both. A complete discussion about interaction and accessibility issues is provided, justifying the presented approach from the point of view of human-environment interaction

Eye-tracking en masse: Group user studies, lab infrastructure, and practices

The costs of eye-tracking technologies steadily decrease. This allows research institutions to obtain multiple eye-tracking devices. Already, several multiple eye-tracker laboratories have been established. Researchers begin to recognize the subfield of group eye-tracking. In comparison to the single-participant eye-tracking, group eye-tracking brings new technical and methodological challenges. Solutions to these challenges are far from being established within the research community. In this paper, we present the Group Studies system, which manages the infrastructure of the group eye-tracking laboratory at the User Experience and Interaction Research Center (UXI) at the Slovak University of Technology in Bratislava. We discuss the functional and architectural characteristics of the system. Furthermore, we illustrate our infrastructure with one of our past studies. With this paper, we also publish the source code and the documentation of our system to be re-used

The Evolution of First Person Vision Methods: A Survey

The emergence of new wearable technologies such as action cameras and smart-glasses has increased the interest of computer vision scientists in the First Person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with First Person Vision recording capabilities. Due to this interest, an increasing demand of methods to process these videos, possibly in real-time, is expected. Current approaches present a particular combinations of different image features and quantitative methods to accomplish specific objectives like object detection, activity recognition, user machine interaction and so on. This paper summarizes the evolution of the state of the art in First Person Vision video analysis between 1997 and 2014, highlighting, among others, most commonly used features, methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart Glasses, Computer Vision, Video Analytics, Human-machine Interactio