Demo Data from EDBT 2026 / reviewers in the wild / expert
Esen Küçüktütüncü
dblp:376/9056
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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.
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality
presence |
0.9 | 1 | 2025 | The Role of Sensorimotor Contingencies and Eye Scanpath Entropy in Presence in Virtual Reality: A Reinforcement Learning Paradigm · IEEE Trans. Vis. Comput. Graph. 2025 |
Methods — techniques the papers use, named apart from their topics
reinforcement learning · 1.7eye scanpath entropy analysis · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | The Role of Sensorimotor Contingencies and Eye Scanpath Entropy in Presence in Virtual Reality: A Reinforcement Learning ParadigmabstractSensorimotor contingencies (SC) refer to the rules by which we use our body to perceive. It has been argued that to the extent that a virtual reality (VR) application affords natural SC so the greater likelihood that participants will experience Place Illusion (PI), the illusion of 'being there' (a component of presence) in the virtual environment. However, notwithstanding numerous studies this only has anecdotal support. Here we used a reinforcement learning (RL) paradigm where 26 participants experienced a VR scenario where the RL agent could sequentially propose changes to 5 binary factors: mono or stereo vision, 3 or 6 degrees of freedom head tracking, mono or spatialised sound, low or high display resolution, or one of two color schemes. The first 4 are SC, whereas the last is not. Participants could reject or accept each change proposed by the RL, until convergence. Participants were more likely to accept changes from low to high SC than changes to the color. Additionally, theory suggests that increased PI should be associated with lower eye scanpath entropy. Our results show that mean entropy did decrease over time and the final level of entropy was negatively correlated with a post exposure questionnaire-based assessment of PI. Esen Küçüktütüncü, Francisco Macía Varela 0001, Joan Llobera, Mel Slater |
IEEE Trans. Vis. Comput. Graph. | 1 |