Browsing by Author "Kán, Peter"

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    Egocentric Network Exploration for Immersive Analytics
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Sorger, Johannes; Arleo, Alessio; Kán, Peter; Knecht, Wolfgang; Waldner, Manuela; Zhang, Fang-Lue and Eisemann, Elmar and Singh, Karan
    To exploit the potential of immersive network analytics for engaging and effective exploration, we promote the metaphor of ''egocentrism'', where data depiction and interaction are adapted to the perspective of the user within a 3D network. Egocentrism has the potential to overcome some of the inherent downsides of virtual environments, e.g., visual clutter and cyber-sickness. To investigate the effect of this metaphor on immersive network exploration, we designed and evaluated interfaces of varying degrees of egocentrism. In a user study, we evaluated the effect of these interfaces on visual search tasks, efficiency of network traversal, spatial orientation, as well as cyber-sickness. Results show that a simple egocentric interface considerably improves visual search efficiency and navigation performance, yet does not decrease spatial orientation or increase cyber-sickness. An occlusion-free Ego-Bubble view of the neighborhood only marginally improves the user's performance. We tie our findings together in an open online tool for egocentric network exploration, providing actionable insights on the benefits of the egocentric network exploration metaphor
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    Embodied Conversational Agents with Situation Awareness for Training in Virtual Reality
    (The Eurographics Association, 2023) Kán, Peter; Rumpelnik, Martin; Kaufmann, Hannes; Jean-Marie Normand; Maki Sugimoto; Veronica Sundstedt
    Embodied conversational agents have a great potential in virtual reality training applications. This paper investigates the impact of conversational agents on users in a first responder training scenario. We integrated methods for automatic speech recognition and speech synthesis with natural language processing into a VR training application in the Unity game engine. Additionally, we present a method for enabling situation awareness for agents in a virtual environment. Finally, we conducted a between-subject lab experiment with 24 participants which investigated differences between conversational agents and agents with pre-scripted audio. Several metrics were measured in the experiment including presence, subjective task performance, learning outcome, interaction quality, quality of information presentation, perceived realism, co-presence, and training task duration. Our results suggest that users trying our conversational agents condition experienced significantly higher level of copresence than users with pre-scripted audio. Additionally, significant differences in subjective task performance and training duration were discovered between genders. Based on the results of our qualitative analysis, we provide guidelines that can facilitate future design of VR training applications and research studies with embodied conversational agents.