Demo Data from EDBT 2026 / reviewers in the wild / expert
Bastien Mourgue
dblp:225/9926
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 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.
| Artificial intelligence
1 paper |
Video understanding and tracking · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 100% | |
| Computer graphics and multimedia
1 paper |
Audio and music processing · 100% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking › object tracking › multi-modal tracking
audio-visual tracking |
0.4 | 1 | 2019 | Audio-Visual Variational Fusion for Multi-Person Tracking with Robots · ACM Multimedia 2019 |
Computer vision › Video understanding and tracking › multi-object tracking
multi-person tracking |
0.4 | 1 | 2019 | Audio-Visual Variational Fusion for Multi-Person Tracking with Robots · ACM Multimedia 2019 |
Methods — techniques the papers use, named apart from their topics
variational fusion · 1.1audio-visual fusion · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Audio-Visual Variational Fusion for Multi-Person Tracking with RobotsabstractRobust multi-person tracking with robots opens the door to analysing engagement and social signals in real-world environments. Multi-person scenarios are charaterised by (i) a time-varying number of people, (ii) intermittent auditory (\eg speech turns) and visual cues (\eg person appearing/disappearing) and (iii) impact of the robot actions in perception. The various sensors (cameras and microphones) available for perception, provide a rich flow of information of intermittent and complementary nature. How to jointly exploit these cues to tackle the multi-person tracking problem with an autonomous system has been an intense research line of the Perception Team in the past few years. In this demo we want to present our, now mature, achievements in the field, and demonstrate two robotic systems able to track multiple persons using auditory and visual cues, when they are available. We will bring the two robots and the necessary computing resources with us, as well as the required presentation materials to discuss the models, methods and tools supporting this technology with the attendants. Xavier Alameda-Pineda, Soraya Arias, Yutong Ban, Guillaume Delorme 0002, Laurent Girin, Radu Horaud, Xiaofei Li 0001, Bastien Mourgue, Guillaume Sarrazin |
ACM Multimedia | 8 |