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Robin Tournemenne

dblp:02/10574 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0003-2732-9925ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 3

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
Audio and music processing · 62% Virtual and augmented reality · 19% Multimedia analysis and retrieval · 19%
Human-computer interaction and pervasive computing
1 paper
Learning and educational technologies · 100%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › music information retrieval
beat tracking
0.112011
An audio-driven virtual dance-teaching assistant · ACM Multimedia 2011
Audio and music processing
music analysis
0.112011
An audio-driven virtual dance-teaching assistant · ACM Multimedia 2011
Audio and music processing
source separation
0.112011
An audio-driven virtual dance-teaching assistant · ACM Multimedia 2011
Audio and music processing › music analysis
multimodal music analysis
0.012011
Enhanced visualisation of dance performance from automatically synchronised multimodal recordings · ACM Multimedia 2011
Learning and educational technologies › embodied learning
dance education
0.012011
An audio-driven virtual dance-teaching assistant · ACM Multimedia 2011

Methods — techniques the papers use, named apart from their topics

source separation · 0.2remastering · 0.2dance step segmentation · 0.2temporal synchronisation · 0.1multimodal fusion · 0.1
YearPublicationVenuePosition
2012 An advanced virtual dance performance evaluator
abstract
The ever increasing availability of high speed Internet access has led to a leap in technologies that support real-time realistic interaction between humans in online virtual environments. In the context of this work, we wish to realise the vision of an online dance studio where a dance class is to be provided by an expert dance teacher and to be delivered to online students via the web. In this paper we study some of the technical issues that need to be addressed in this challenging scenario. In particular, we describe an automatic dance analysis tool that would be used to evaluate a student's performance and provide him/her with meaningful feedback to aid improvement.
Slim Essid, Dimitrios S. Alexiadis, Robin Tournemenne, Marc Gowing, Philip Kelly, David S. Monaghan, Petros Daras, Angélique Dremeau, Noel E. O'Connor
ICASSP3
2011 An audio-driven virtual dance-teaching assistant
abstract
This work addresses the Huawei/3Dlife Grand challenge proposing a set of audio tools for a virtual dance-teaching assistant. These tools are meant to help the dance student develop a sense of rhythm to correctly synchronize his/her movements and steps to the musical timing of the choreographies to be executed. They consist of three main components, namely a music (beat) analysis module, a source separation and remastering module and a dance step segmentation module. These components enable to create augmented tutorial videos highlighting the rhythmic information using, for instance, a synthetic dance teacher voice, but also videos highlighting the steps executed by a student to help in the evaluation of his/her performance.
Slim Essid, Yves Grenier, Mounira Maazaoui, Gaël Richard, Robin Tournemenne
ACM Multimedia5
2011 Enhanced visualisation of dance performance from automatically synchronised multimodal recordings
abstract
The Huawei/3DLife Grand Challenge Dataset provides multimodal recordings of Salsa dancing, consisting of audiovisual streams along with depth maps and inertial measurements. In this paper, we propose a system for augmented reality-based evaluations of Salsa dancer performances. An essential step for such a system is the automatic temporal synchronisation of the multiple modalities captured from different sensors, for which we propose efficient solutions. Furthermore, we contribute modules for the automatic analysis of dance performances and present an original software application, specifically designed for the evaluation scenario considered, which enables an enhanced dance visualisation experience, through the augmentation of the original media with the results of our automatic analyses.
Marc Gowing, Philip Kelly, Noel E. O'Connor, Cyril Concolato, Slim Essid, Jean Le Feuvre, Robin Tournemenne, Ebroul Izquierdo, Vlado Kitanovski, Qianni Zhang
ACM Multimedia7