Julian Britten

dblp:329/1162 · DBLP profile ↗
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4ranked-venue papers
0as first author
4since 2021 · last 2026
0000-0002-2646-2727ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 4 · 4 since 2021
YearPublicationVenuePosition
2026 MIRAGE: Enabling Real-Time Automotive Mediated Reality
abstract
Traffic is inherently dangerous, with around 1.19 million fatalities annually. Automotive Mediated Reality (AMR) can enhance driving safety by overlaying critical information (e.g., outlines, icons, text) on key objects to improve awareness, altering objects’ appearance to simplify traffic situations, and diminishing their appearance to minimize distractions. However, real-world AMR evaluation remains limited due to technical challenges. To fill this sim-to-real gap, we present MIRAGE, an open-source tool that enables real-time AMR in real vehicles. MIRAGE implements 15 effects across the AMR spectrum of augmented, diminished, and modified reality using state-of-the-art computational models for object detection and segmentation, depth estimation, and inpainting. In an on-road expert user study (N=9) of MIRAGE, participants enjoyed the AMR experience while pointing out technical limitations and identifying use cases for AMR. We discuss these results in relation to prior work and outline implications for AMR ethics and interaction design.
Pascal Jansen, Julian Britten, Mark Colley, Markus Sasalovici, Enrico Rukzio
CHI2
2025 PlantPal: Leveraging Precision Agriculture Robots to Facilitate Remote Engagement in Urban Gardening
Albin Zeqiri, Julian Britten, Clara Schramm, Pascal Jansen, Michael Rietzler, Enrico Rukzio
CHI2
2025 AirClick: Modularized Interactive Inflatables for On-Demand Room Transformation
abstract
As living and working spaces become scarce and costly, interiors transitioning between living, working, and sleeping configurations while enabling customized setups are in demand. Traditional furniture consumes space and is cumbersome to rearrange. Shape-changing furniture could solve this, yet existing options lack resolution, stability, or adaptability. We present AirClick, which facilitates on-demand room transformation using modular interactive inflatables. Our fabrication process supports personally fabricated and retrofitted retail inflatables. The touch-actuated modules connect to a floor-based air connector grid, facilitating interaction while integrating with traditional furniture. In a lab study (N=20) across four scenarios (office, meeting room, apartment room, multipurpose hall), participants rapidly transformed rooms and perceived AirClick as significantly more usable with higher intention to use in the everyday scenarios than in the hall, indicating suitability for routine activities with low to medium requirements for robustness. User feedback highlights AirClick ’s usefulness and scalability in diverse settings, hence showing AirClick’s space-saving and customizable design can enhance the functionality and adaptability of living and working spaces.
Pascal Jansen, Benno Hölz, Julian Britten, Mark Colley, Enrico Rukzio
MUM3
2023 AutoVis: Enabling Mixed-Immersive Analysis of Automotive User Interface Interaction Studies
abstract
Automotive user interface (AUI) evaluation becomes increasingly complex due to novel interaction modalities, driving automation, heterogeneous data, and dynamic environmental contexts. Immersive analytics may enable efficient explorations of the resulting multilayered interplay between humans, vehicles, and the environment. However, no such tool exists for the automotive domain. With AutoVis, we address this gap by combining a non-immersive desktop with a virtual reality view enabling mixed-immersive analysis of AUIs. We identify design requirements based on an analysis of AUI research and domain expert interviews (N=5). AutoVis supports analyzing passenger behavior, physiology, spatial interaction, and events in a replicated study environment using avatars, trajectories, and heatmaps. We apply context portals and driving-path events as automotive-specific visualizations. To validate AutoVis against real-world analysis tasks, we implemented a prototype, conducted heuristic walkthroughs using authentic data from a case study and public datasets, and leveraged a real vehicle in the analysis process.
Pascal Jansen, Julian Britten, Alexander Häusele, Thilo Segschneider, Mark Colley, Enrico Rukzio
CHI2