Demo Data from EDBT 2026 / reviewers in the wild / expert
Natalia Ocampo
dblp:420/7804
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2025
—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 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 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.
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 87% Usability and user experience research · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Immersive interaction › avatar
avatar representation |
0.9 | 1 | 2025 | Comparing Hand and Controller Avatars with Hand Tracking and Controller-Based Interaction · ISMAR 2025 |
Immersive interaction › 3d user interface
virtual reality input |
0.9 | 1 | 2025 | Comparing Hand and Controller Avatars with Hand Tracking and Controller-Based Interaction · ISMAR 2025 |
Methods — techniques the papers use, named apart from their topics
user study · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Comparing Hand and Controller Avatars with Hand Tracking and Controller-Based InteractionabstractPrevious research suggests that the congruency between common VR input devices - such as controllers or hand tracking - and their visual representations (e.g., hand or controller avatars) influences user experience and performance. However, the specific effects of input-avatar combinations remain underexplored. We study the effects of common input devices (hand tracking and controllers) and visual representations (hand and controller avatars) on performance and perceived success in target acquisition tasks. We included both grasping and pinching gestures across 16 combinations of input, avatar, and target size. Results indicate that hand tracking benefits from any form of visual representation-even when mismatched-achieving up to 5.8% greater accuracy compared to having no avatar, likely due to its reliance on visual feedback in the absence of a physical prop. Controllers were generally preferred and offered faster task completion. However, mismatched avatars had a stronger negative effect with controllers, particularly when the virtual gesture did not align with the physical action, leading to a 5.6% drop in accuracy compared to the matched condition-suggesting that inaccurate feedback can be more disruptive than having no avatar feedback at all. Natalia Ocampo, Johann Felipe Gonzalez Avila, Robert J. Teather |
ISMAR | 1 |