VLDB 2026 Research / reviewers in the wild / expert
David Mertens
dblp:11/9595
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
—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 · 50% Haptics and multimodal interaction · 50% | |
| Computer graphics and multimedia
1 paper |
Geometric modeling and processing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Immersive interaction
mixed reality |
1.0 | 1 | 2026 | Aligning Realities: A Registration Pipeline for Arbitrary Objects in Mixed Reality Using Controller-Based Point Selection · VR 2026 |
Geometric modeling and processing
registration |
0.3 | 1 | 2026 | Aligning Realities: A Registration Pipeline for Arbitrary Objects in Mixed Reality Using Controller-Based Point Selection · VR 2026 |
Methods — techniques the papers use, named apart from their topics
point-to-point matching · 2.0motion capture · 2.0kabsch algorithm · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Aligning Realities: A Registration Pipeline for Arbitrary Objects in Mixed Reality Using Controller-Based Point SelectionabstractA wide range of Mixed Reality (MR) applications rely on haptic interaction with real-world objects. These interactions range from grasping and standing on objects, to writing on their surfaces. Accurate alignment of a real-world object with its virtual counterpart enables users to perceive and interact with it both visually and haptically. However, existing registration methods often rely on tracked, external markers, are geometrically constrained, or require complex setups that limit their practical applicability. Hence, we present an integrated pipeline for rapid and accurate registration of arbitrary physical objects in MR. The proposed approach combines custom 3D-printed add-ons for Meta Quest 3 controllers with a point-to-point matching algorithm based on Kabsch optimization, enabling precise selection, calibration, and registration. The method is objectively evaluated using a modern motion capture rig against other state-of-the-art registration techniques. An additional user-centric evaluation helps to understand the general usability of our pipeline. Source code and datasets are released as open resources to encourage reproducibility and further research. David Mertens, Steffen-Sascha Stein, Kristoffer Waldow, Arnulph Fuhrmann |
VR | 1 |