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Daniel Cernea
Researcher at Kaiserslautern University of Technology
Publications - 33
Citations - 832
Daniel Cernea is an academic researcher from Kaiserslautern University of Technology. The author has contributed to research in topics: Visualization & Information visualization. The author has an hindex of 11, co-authored 32 publications receiving 721 citations. Previous affiliations of Daniel Cernea include Linnaeus University & Jacobs University Bremen.
Papers
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Journal ArticleDOI
Collaborative visualization: definition, challenges, and research agenda
TL;DR: The purpose of this article is to help pinpoint the unique focus of collaborative visualization with its specific aspects, challenges, and requirements within the intersection of general computer-supported cooperative work and visualization research, and to draw attention to important future research questions to be addressed by the community.
Journal ArticleDOI
Fluid interaction for information visualization
Niklas Elmqvist,Andrew Vande Moere,Hans-Christian Jetter,Daniel Cernea,Harald Reiterer,T. J. Jankun-Kelly +5 more
TL;DR: This article collects examples of visualizations with ‘best-in-class’ interaction and uses them to extract practical design guidelines for future designers and researchers to address the issue of interaction in visualization.
Book ChapterDOI
Real-Time scale invariant 3d range point cloud registration
TL;DR: This paper proposes an approach which enables SIFT application to locate scale and rotation invariant features in 3D point clouds and utilizes the known point correspondence registration algorithm in order to achieve real-time registration of 3Dpoint clouds.
Detecting Insight and Emotion in Visualization Applications with a Commercial EEG Headset
TL;DR: It is argued that measuring emotional responses via EEG during an insight-related problem solving results in non-intrusive, nearly automatic detection of the major Aha! moments the user experiences, and opens the door for the objective evaluation and comparison of various visualizations techniques.
Journal ArticleDOI
A survey of technologies on the rise for emotion-enhanced interaction ☆
TL;DR: This paper highlights techniques that have been employed more intensely for emotion measurement in the context of affective interaction, and presents relevant applications and establishes a categorization of the roles of emotion detection in interaction.