Demo Data from VLDB 2026 / reviewers in the wild / expert
Girish Acharya
dblp:153/5875
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1Human-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
1 paper |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Wearable and physiological sensing · 33% Immersive interaction · 33% Human-AI interaction · 33% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality
augmented reality |
0.2 | 1 | 2014 | AR-mentor: Augmented reality based mentoring system · ISMAR 2014 |
Virtual and augmented reality › augmented reality
augmented reality assistance |
0.2 | 1 | 2014 | AR-mentor: Augmented reality based mentoring system · ISMAR 2014 |
Immersive interaction › see-through display
optical see-through display |
0.1 | 1 | 2014 | AR-mentor: Augmented reality based mentoring system · ISMAR 2014 |
Human-AI interaction › intelligent assistant
virtual assistants |
0.1 | 1 | 2014 | AR-mentor: Augmented reality based mentoring system · ISMAR 2014 |
Wearable and physiological sensing
wearable display |
0.1 | 1 | 2014 | AR-mentor: Augmented reality based mentoring system · ISMAR 2014 |
Methods — techniques the papers use, named apart from their topics
pose tracking · 0.4natural language interaction · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | AR-mentor: Augmented reality based mentoring systemabstractAR-Mentor is a wearable real time Augmented Reality (AR) mentoring system that is configured to assist in maintenance and repair tasks of complex machinery, such as vehicles, appliances, and industrial machinery. The system combines a wearable Optical-See-Through (OST) display device with high precision 6-Degree-Of-Freedom (DOF) pose tracking and a virtual personal assistant (VPA) with natural language, verbal conversational interaction, providing guidance to the user in the form of visual, audio and locational cues. The system is designed to be heads-up and hands-free allowing the user to freely move about the maintenance or training environment and receive globally aligned and context aware visual and audio instructions (animations, symbolic icons, text, multimedia content, speech). The user can interact with the system, ask questions and get clarifications and specific guidance for the task at hand. A pilot application with AR-Mentor was successfully built to instruct a novice to perform an advanced 33-step maintenance task on a training vehicle. The initial live training tests demonstrate that AR-Mentor is able to help and serve as an assistant to an instructor, freeing him/her to cover more students and to focus on higher-order teaching. Vlad Branzoi, Michael Wolverton, Glenn Murray, Nicholas Vitovitch, Louise Yarnall, Girish Acharya, Supun Samarasekera, Rakesh Kumar 0001 |
ISMAR | 7 |