Demo Data from SIGIR 2026 / reviewers in the wild / expert
Thomas Calloway
dblp:153/6010
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2Human-computer interaction and ubiquitous computing · 1
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
2 papers |
Virtual and augmented reality · 80% Geometric modeling and processing · 20% | |
| Human-computer interaction and pervasive computing
1 paper |
Wearable and physiological sensing · 100% |
Topics — the 6 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing › registration
augmented reality registration |
0.2 | 1 | 2015 | Design and Error Analysis of a Vehicular AR System with Auto-Harmonization · IEEE Trans. Vis. Comput. Graph. 2015 |
Virtual and augmented reality › augmented reality
augmented reality system |
0.2 | 1 | 2015 | Design and Error Analysis of a Vehicular AR System with Auto-Harmonization · IEEE Trans. Vis. Comput. Graph. 2015 |
Virtual and augmented reality › augmented reality › automotive augmented reality
in-car augmented reality |
0.2 | 1 | 2015 | Design and Error Analysis of a Vehicular AR System with Auto-Harmonization · IEEE Trans. Vis. Comput. Graph. 2015 |
Virtual and augmented reality
augmented reality |
0.2 | 1 | 2014 | Improved registration for vehicular AR using auto-harmonization · ISMAR 2014 |
Virtual and augmented reality
calibration and registration |
0.2 | 1 | 2014 | Improved registration for vehicular AR using auto-harmonization · ISMAR 2014 |
Virtual and augmented reality › augmented reality
optical see-through head-mounted display |
0.1 | 1 | 2015 | Design and Error Analysis of a Vehicular AR System with Auto-Harmonization · IEEE Trans. Vis. Comput. Graph. 2015 |
Methods — techniques the papers use, named apart from their topics
sensor fusion · 0.4optical see-through HMD · 0.4auto-harmonization · 0.4optical-inertial hybrid tracking · 0.2covariance analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Design and Error Analysis of a Vehicular AR System with Auto-HarmonizationabstractThis paper describes the design, development and testing of an AR system that was developed for aerospace and ground vehicles to meet stringent accuracy and robustness requirements. The system uses an optical see-through HMD, and thus requires extremely low latency, high tracking accuracy and precision alignment and calibration of all subsystems in order to avoid mis-registration and "swim". The paper focuses on the optical/inertial hybrid tracking system and describes novel solutions to the challenges with the optics, algorithms, synchronization, and alignment with the vehicle and HMD systems. Tracker accuracy is presented with simulation results to predict the registration accuracy. A car test is used to create a through-the-eyepiece video demonstrating well-registered augmentations of the road and nearby structures while driving. Finally, a detailed covariance analysis of AR registration error is derived. Eric Foxlin, Thomas Calloway |
IEEE Trans. Vis. Comput. Graph. | 2 |
| 2014 | Improved registration for vehicular AR using auto-harmonizationabstractThis paper describes the design, development and testing of an AR system that was developed for aerospace and ground vehicles to meet stringent accuracy and robustness requirements. The system uses an optical see-through HMD, and thus requires extremely low latency, high tracking accuracy and precision alignment and calibration of all subsystems in order to avoid mis-registration and “swim”. The paper focuses on the optical/inertial hybrid tracking system and describes novel solutions to the challenges with the optics, algorithms, synchronization, and alignment with the vehicle and HMD systems. A system accuracy analysis is presented with simulation results to predict the registration accuracy. Finally, a car test is used to create a through-the-eyepiece video demonstrating well-registered augmentations of the road and nearby structures while driving. Eric Foxlin, Thomas Calloway |
ISMAR | 2 |