Visual Decoding of Targets During Visual Search From Human Eye Fixations

What does human gaze reveal about a users' intents and to which extend can these intents be inferred or even visualized? Gaze was proposed as an implicit source of information to predict the target of visual search and, more recently, to predict the object class and attributes of the search target. In this work, we go one step further and investigate the feasibility of combining recent advances in encoding human gaze information using deep convolutional neural networks with the power of generative image models to visually decode, i.e. create a visual representation of, the search target. Such visual decoding is challenging for two reasons: 1) the search target only resides in the user's mind as a subjective visual pattern, and can most often not even be described verbally by the person, and 2) it is, as of yet, unclear if gaze fixations contain sufficient information for this task at all. We show, for the first time, that visual representations of search targets can indeed be decoded only from human gaze fixations. We propose to first encode fixations into a semantic representation and then decode this representation into an image. We evaluate our method on a recent gaze dataset of 14 participants searching for clothing in image collages and validate the model's predictions using two human studies. Our results show that 62% (Chance level = 10%) of the time users were able to select the categories of the decoded image right. In our second studies we show the importance of a local gaze encoding for decoding visual search targets of use

A methodological framework for capturing relative eyetracking coordinate data to determine gaze patterns and fixations from two or more observers

While physical activity during cancer treatment is found beneficial for breast cancer patients, evidence indicates ambiguous findings concerning effects of scheduled exercise programs on treatment-related symptoms. This study investigated effects of a scheduled home-based exercise intervention in breast cancer patients during adjuvant chemotherapy, on cancer-related fatigue, physical fitness, and activity level. Sixty-seven women were randomized to an exercise intervention group (n=33, performed strength training 3x/week and 30 minutes brisk walking/day) and a control group (n=34, performed their regular physical activity level). Data collection was performed at baseline, at completion of chemotherapy (Post1), and 6-month postchemotherapy (Post2). Exercise levels were slightly higher in the scheduled exercise group than in the control group. In both groups, cancer-related fatigue increased at Post1 but returned to baseline at Post2. Physical fitness and activity levels decreased at Post1 but were significantly improved at Post2. Significant differences between intervention and control groups were not found. The findings suggest that generally recommended physical activity levels are enough to relief cancer-related fatigue and restore physical capacity in breast cancer patients during adjuvant chemotherapy, although one cannot rule out that results reflect diminishing treatment side effects over time

Contextualizing the blogosphere: A comparison of traditional and novel user interfaces for the web

In this paper, we investigate how contextual user interfaces affect blog reading experience. Based on a review of previous research, we argue why and how contextualization may result in (H1) enhanced blog reading experiences. In an eyetracking experiment, we tested 3 different web-based user interfaces for information spaces. The StarTree interface (by Inxight) and the Focus-Metaphor interface are compared with a standard blog interface. Information tasks have been used to evaluate and compare task performance and user satisfaction between these three interfaces. We found that both contextual user interfaces clearly outperformed the traditional blog interface, both in terms of task performance as well as user satisfaction. © 2007 Laqua, S., Ogbechie, N. and Sasse, M. A

'There's more than meets the eye': analysing verbal protocols, gazes and sketches on external mathematical representations

When learners are asked to verbalise their thoughts about multiple mathematical representations, some researchers are left to analyse utterances based on video records of activity which may have ambiguous signifiers. They are also faced with post hoc analysis of paper-based worksheets, in which temporal order has to be guessed. In this paper, attempts to minimise such methodological problems by means of recent technologies such as eye-tracking, tablet PC screen capture, digital video cameras and the latest video analysis tools are illustrated in the context of a study of the effect of varying representational instantiations on learners' problem-solving strategies