Intuitive visualization technique to support eye tracking data analysis: A user-study

While fixation distribution is conventionally visualized using heat maps, there is still a lack of a commonly accepted technique to visualize saccade distributions. Inspired by wind maps and the Oriented Line Integral Convolution (OLIC) technique, we visualize saccades by drawing ink droplets which follow the direction indicated by a flow direction map. This direction map is computed using a kernel density estimation technique over the tangent directions to each saccade gaze point. The image is further blended with the corresponding heat map. It results in an animation or a static image showing main directions of the transitions between different areas of interest. We also present results from a web-based user study where naive non-expert users where asked to identify the direction of the flow and simple patterns. The results showed that these visualizations can successfully be used to support visual analysis of the eye-tracking data. It also showed that the use of animation allows to ease the task and to improve the performance

Preparing for Perceptual Studies: Position and Orientation of Wrist-worn Smartwatches for Reading Tasks

International audienceDespite the increasing demand for data visualization on mobile devices with small displays, few guidelines exist for designing visualizations for this form factor. To conduct perceptual studies with smartwatches under realistic conditions , we first need to know how to position these devices in front of a viewer. We report the results of a study, in which we investigate how people hold their smartwatches to read information. This is the first in a series of studies we are conducting to understand the perception of visualizations on smartwatches. Our study results show that people hold their watches at a distance of 28 cm in front of them, at a pitch angle of ~50 degrees, and at an angle of ~10 degrees from the line of sight

Reflections on Visualization in Motion for Fitness Trackers

International audienceIn this paper, we reflect on our past work towards understanding how to design visualizations for fitness trackers that are used in motion. We have coined the term "visualization in motion" for visualizations that are used in the presence of relative motion between a viewer and the visualization. Here, we describe how visualization in motion is relevant to sports scenarios. We also provide new data on current smartwatch visualizations for sports and discuss future challenges for visualizations in motion for fitness trackers

Eye-tracking based analysis concept for the evaluation of visualizations

Das Ziel einer Eyetracking-Benutzerstudie ist die Untersuchung und Auswertung einer Forschungsfragestellung anhand von aufgenommen Eyetracking-Daten mit Hilfe von Metriken, statistischen Berechnungen und Visualisierungen. Meist müssen anschließend die Ergebnisse in einem Bericht festgehalten und veröffentlicht werden. Ein Großteil des Arbeitsaufwandes bei einer Auswertung wird in manuelle Aufgaben wie das Eingeben von Fragebögen und Antworten, das Sortieren der Daten, das Durchführen von statistischen Tests und die Erstellung von Visualisierungen aufgewendet. In dieser Diplomarbeit wird ein Konzept für ein Framework vorgestellt, welches auf dem Visual Information Seeking Mantra basiert. Das Framework soll den Benutzer bei der Erstellung, Durchführung und Auswertung einer Eyetracking-Benutzerstudie unterstützen. Dafür werden die Eyetracking- und Probandendaten in einer Datenbank gespeichert und es werden verschiedene Metriken, Statistiken und Visualisierungen zur Verfügung gestellt, die der Benutzer für die Auswertung verwenden kann. Die Ergebnisse aller Berechnungen werden in einer Datenbank gespeichert, so dass der Benutzer die Berechnungen zu späteren Zeitpunkten zur Verfügung hat. Das Framework kann außerdem den Fragebogen der Probanden auswerten und einen Bericht in LaTeX erstellen, welcher die Probandendaten, Boxplotdiagramme und Heatmaps enthält

A Comparison of a Transition-based and a Sequence-based Analysis of AOI Transition Sequences

Several visual analytics (VA) systems are used for analyzing eye-tracking data because they synergize human-in-the-loop exploration with speed and accuracy of the computer. In the VA systems, the choices of visualization techniques could afford discovering certain types of insights while hindering others. Understanding these affordances and hindrances is essential to design effective VA systems. In this paper, we focus on two approaches for visualizing AOI transitions: the transition based approach (exemplified by the radial transition graph, RTG) and the sequence-based approach (exemplified by the Alpscarf). We captured the insights generated by two analysts who individually use each visualization technique on the same dataset. Based on the results, we identify four phases of analytic activities and discuss opportunities that the two visualization approaches can complement each other. We point out design implications for VA systems that combine these visualization approaches

A Replication Study on Glanceable Visualizations: Comparing Different Stimulus Sizes on a Laptop Computer

International audienceWe replicated a smartwatch perception experiment on the topic of glanceable visualizations. The initial study used a setup that involved showing stimuli on an actual smartwatch attached to a wooden stand and a laptop to run and log the experiment and communicate with the smartwatch. In our replication we wanted to test whether a much simpler setup that involved showing the same stimuli on a laptop screen with similar pixel size and density would lead to similar results. We also extended the initial study by testing to what extent the size of the stimulus played a role for the results. Our results indicate that the general trends observed in the original study mostly held also on the larger display, with only a few differences in certain conditions. Yet, participants were slower on the large display. We also found no evidence of a difference for the two different stimulus display sizes we tested. Our study, thus, gives evidence that simulating smartwatch displays on laptop screens with similar resolution and pixel size might be a viable alternative for smartwatch perception studies with visualizations

A Survey on Sleep Visualizations for Fitness Trackers

International audienceWe contribute the results of an exploratory study and a survey on visualizations for fitness trackers. Fitness trackers are becoming ubiquitous trackers of personal data. They often come with small attached displays that show micro visualizations of data such as heart rate, step counts, sleep duration, or number of floors climbed. Unfortunately, little is known about how wearers of fitness trackers use and perceive these micro visualizations. To collect data on the use of fitness visualizations, we conducted ten personal interviews with regular wearers of fitness trackers. Inspired by frequent responses regarding sleep tracking, we deployed an online questionnaire specifically on sleep visualizations for fitness trackers. Our results show that most participants were interested particularly in seeing previous night's sleep data on their fitness trackers and preferred visualizations that were easy to read like the hypnogram and bar as well as donut charts for sleep phases and duration

Context Specific Visualizations on Smartwatches

International audienceWe present an analysis of the results of a full-day context-specific ideation exercise for smartwatch visualizations. Participants of the exercise created 34 sketches during a sightseeing activity. Our analysis of these sketches showed where visualizations could be applied and shown, what information needs they could target, and how data could be represented in the sightseeing context. Supplementary material is available at-https://osf.io/vhn43/

Classification of strategies for solving programming problems using Aol sequence analysis

This eye tracking study examines participants’ visual attention when solving algorithmic problems in the form of programming problems. The stimuli consisted of a problem statement, example output, and a set of multiple-choice questions regarding variables, data types, and operations needed to solve the programming problems. We recorded eye movements of students and performed an Area of Interest (AoI) sequence analysis to identify reading strategies in terms of participants’ performance and visual effort. Using classical eye tracking metrics and a visual AoI sequence analysis we identified two main groups of participants—effective and ineffective problem solvers. This indicates that diversity of participants’ mental schemas leads to a difference in their performance. Therefore, identifying how participants’ reading behavior varies at a finer level of granularity warrants further investigation