Demo Data from EDBT 2026 / reviewers in the wild / expert
Miriam Kurz
dblp:270/2597
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 77% Usability and user experience research · 23% | |
| Computer graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Audio and music processing
audio quality assessment |
0.6 | 1 | 2022 | Comparing Direct and Indirect Methods of Audio Quality Evaluation in Virtual Reality Scenes of Varying Complexity · IEEE Trans. Vis. Comput. Graph. 2022 |
Immersive interaction
virtual reality interaction |
0.6 | 1 | 2022 | Comparing Direct and Indirect Methods of Audio Quality Evaluation in Virtual Reality Scenes of Varying Complexity · IEEE Trans. Vis. Comput. Graph. 2022 |
Methods — techniques the papers use, named apart from their topics
rank-order elimination · 1.1pairwise comparison · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Comparing Direct and Indirect Methods of Audio Quality Evaluation in Virtual Reality Scenes of Varying ComplexityabstractMany quality evaluation methods are used to assess uni-modal audio or video content without considering perceptual, cognitive, and interactive aspects present in virtual reality (VR) settings. Consequently, little is known regarding the repercussions of the employed evaluation method, content, and subject behavior on the quality ratings in VR. This mixed between- and within-subjects study uses four subjective audio quality evaluation methods (viz. multiple-stimulus with and without reference for direct scaling, and rank-order elimination and pairwise comparison for indirect scaling) to investigate the contributing factors present in multi-modal 6-DoF VR on quality ratings of real-time audio rendering. For each between-subjects employed method, two sets of conditions in five VR scenes were evaluated within-subjects. The conditions targeted relevant attributes for binaural audio reproduction using scenes with various amounts of user interactivity. Our results show all referenceless methods produce similar results using both condition sets. However, rank-order elimination proved to be the fastest method, required the least amount of repetitive motion, and yielded the highest discrimination between spatial conditions. Scene complexity was found to be a main effect within results, with behavioral and task load index results implying more complex scenes and interactive aspects of 6-DoF VR can impede quality judgments. Thomas Robotham, Olli Rummukainen, Miriam Kurz, Marie Eckert, Emanuël A. P. Habets |
IEEE Trans. Vis. Comput. Graph. | 3 |