Visual exploration of eye movement data using the Space-Time-Cube

Eye movement recordings produce large quantities of spatio- temporal data, and are more and more frequently used as an aid to gain further insight into human thinking in usability studies in GIScience domain among others. After reviewing some common visualization methods for eye movement data, the limitations of these methods are discussed. This paper proposes an approach that enables the use of the Space-Time-Cube (STC) for representation of eye movement recordings. Via interactive functions in the STC, spatiotemporal patterns in eye movement data could be analyzed. A case study is presented according to proposed solutions for eye movement data analysis. Finally, the advantages and limitations of using the STC to visually analyze eye movement recordings are summarized and discussed

EXPLORING THE IMPACT OF VISUAL COMPLEXITY LEVELS IN 3D CITY MODELS ON THE ACCURACY OF INDIVIDUALS’ ORIENTATION AND COGNITIVE MAPS

In this paper we report results from a qualitative user experiment (n=107) designed to contribute to understanding the impact of various levels of complexity (mainly based on levels of detail, i.e., LoD) in 3D city models, specifically on the participants’ orientation and cognitive (mental) maps. The experiment consisted of a number of tasks motivated by spatial cognition theory where participants (among other things) were given orientation tasks, and in one case also produced sketches of a path they ‘travelled’ in a virtual environment. The experiments were conducted in groups, where individuals provided responses on an answer sheet. The preliminary results based on descriptive statistics and qualitative sketch analyses suggest that very little information (i.e., a low LoD model of a smaller area) might have a negative impact on the accuracy of cognitive maps constructed based on a virtual experience. Building an accurate cognitive map is an inherently desired effect of the visualizations in planning tasks, thus the findings are important for understanding how to develop better-suited 3D visualizations such as 3D city models. In this study, we specifically discuss the suitability of different levels of visual complexity for development planning (urban planning), one of the domains where 3D city models are most relevant

Virtual environments as memory training devices in navigational tasks for older adults

Cognitive training approaches using virtual environments (VEs) might counter age-related visuospatial memory decline and associated difficulties in wayfinding. However, the effects of the visual design of a VE in route learning are not fully understood. Therefore, we created a custom-designed VE optimized for route learning, with adjusted levels of realism and highlighted landmark locations (MixedVE). Herein we tested participants’ route recall performance in identifying direction of turn at the intersection with this MixedVE against two baseline alternatives (AbstractVE, RealisticVE). An older vs. a younger group solved the tasks in two stages (immediate vs. delayed recall by one week). Our results demonstrate that the MixedVE facilitates better recall accuracy than the other two VEs for both age groups. Importantly, this pattern persists a week later. Additionally, our older participants were mostly overconfident in their route recall performance, but the MixedVE moderated this potentially detrimental overconfidence. Before the experiment, participants clearly preferred the RealisticVE, whereas after the experiment, most of the younger, and many of the older participants, preferred the MixedVE. Taken together, our findings provide insights into the importance of tailoring visualization design in route learning with VEs. Furthermore, we demonstrate the great potential of the MixedVE and by extension, of similar VEs as memory training devices for route learning, especially for older participants

Space-variant image coding for stereoscopic media

This paper presents a brief overview of space variant image coding for stereoscopic media and reports on findings from a study using foveation for stereoscopic imaging. Foveation is a perceptually motivated approach to image coding based on the structure of human fovea and it is well studied in image and video processing domains. However it is less exploited for three-dimensional (3D) space even though it is potentially well suited also for 3D, e.g. for level of detail management in gaze contingent stereoscopic displays. In this paper results from a stereoscopic foveation implementation is presented in support of this argument. A brief discussion on computational as well as human factors for successful management and presentation of stereoscopic media is also provided based on current literature

Quantifying gaze and mouse interactions on spatial visual interfaces with a new movement analytics methodology

Eye movements provide insights into what people pay attention to, and therefore are commonly included in a variety of human-computer interaction studies. Eye movement recording devices (eye trackers) produce gaze trajectories, that is, sequences of gaze location on the screen. Despite recent technological developments that enabled more affordable hardware, gaze data are still costly and time consuming to collect, therefore some propose using mouse movements instead. These are easy to collect automatically and on a large scale. If and how these two movement types are linked, however, is less clear and highly debated. We address this problem in two ways. First, we introduce a new movement analytics methodology to quantify the level of dynamic interaction between the gaze and the mouse pointer on the screen. Our method uses volumetric representation of movement, the space-time densities, which allows us to calculate interaction levels between two physically different types of movement. We describe the method and compare the results with existing dynamic interaction methods from movement ecology. The sensitivity to method parameters is evaluated on simulated trajectories where we can control interaction levels. Second, we perform an experiment with eye and mouse tracking to generate real data with real levels of interaction, to apply and test our new methodology on a real case. Further, as our experiment tasks mimics route-tracing when using a map, it is more than a data collection exercise and it simultaneously allows us to investigate the actual connection between the eye and the mouse. We find that there seem to be natural coupling when eyes are not under conscious control, but that this coupling breaks down when instructed to move them intentionally. Based on these observations, we tentatively suggest that for natural tracing tasks, mouse tracking could potentially provide similar information as eye-tracking and therefore be used as a proxy for attention. However, more research is needed to confirm this

Review zu: Dimitris Ballas, Danny Droling and Benjamin Hennig, The social atlas of Europe

The Social Atlas of Europe, as the title suggests, takes on a job of mapping social issues in Europe using mainly cartograms. The book includes the European Union (EU) member and candidate countries as well as the European Economic Area (EEA) and the Schengen countries. The thematic coverage is as impressive as the geographic coverage: identity and culture, education, employment, industry and occupation, health, politics, economics, environment, social cohesion and policy; 21 different data sources are listed, among which EU-related official statistics appear to dominate, but the authors also make use of specific studies such as the European Values Survey1 or the very general ones such as the CIA World Factbook2, and occasionally Wikipedia or various newspapers and organizations