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Bastien Mourgue

dblp:225/9926 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Computer vision › Video understanding and tracking › object tracking › multi-modal tracking
audio-visual tracking
0.412019
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
0.412019
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
YearPublicationVenuePosition
2019 Audio-Visual Variational Fusion for Multi-Person Tracking with Robots
abstract
Robust 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 Multimedia8