Thibaut LE NAOUR

Associate Professor (MCF) | Computer science

QUALIFIé CNU 27 et 74

IRISA Laboratory,
University of Southern Brittany,
Bâtiment ENSIbs - Campus de Tohannic,
Rue Yves Mainguy - 56017 Vannes

Hello, I’m Thibaut !
PhD in Computer Graphics specialized in the research area of virtual characters animation. I defended my PhD on 9th of December 2013 under the supervision of Nicolas Courty and Sylvie Gibet (Expression team in Brittany [France]).

Unitil 2019, I was lecturer at the University of Fribourg (Switzerland). I worked on the analysis and synthesis of human movement in the fields of Computer Science and Cognition (movement analysis, motor learning, relationship to others and analysis of perceptual strategies using eye tracking). My main work focuses on the conception, implementation and assessment of HMI models for the learning of motor and perceptual-motor skills. To achieve that, several sub-issues are addressed such as kinematic motion analysis (body and gaze), the conception of efficient IAs dedicated to Human-Avatar interactions, the design of experimental protocols to assess these models as well as the analysis of data resulting from the experiments conducted.

Short CV

Education and works

Business executive of Motion-UP
Motion-Up Vannes (FRANCE)
Associate Professor (MCF)
Supervisor of the Computer Science Master
Catholic University of the West, Vannes (FRANCE)
Coplab, University of Fribourg, Fribourg (Suitzerland)
IUT, University of South Brittany, Vannes (France)
IRISA, University of South Brittany, Vannes (France)
Junior research engineer
VALORIA, University of South Brittany, Vannes (France)
3D Developer
NPCube, Le Port (île de la Réunion - France)
Master in Computer Science
UBS Vannes
Master in Mathematics and application of Mathematics
UBS Vannes


Computer Sciences, 600h, Licence and Master UNIVERSITY & IUT: Rendering, Computer animation, C++, Web programming, Multimedia processing, First-order logic, Algorithmy, IHM
Human Movement Sciences, 560h, Licence and Master Perception, Congition and Control motor, Biomechanics, Motion capture and Eye tracking, Sport Psychology, IHM
Master Thesis Supervision: 27


Programming C/C++, OpenGL & C# Java, Html, Css & Php Javascript / Python Applied mathematics Graph theory, Optimization, Modelisation & simulation, Discrete geometry & 3D applications, Signal processing, 3D Animation, 3D Rendering
SDK / Libraries QT, WxWidgets, SDL, GLFW, SMFL, Eigen, Tetgen, AML++, FBX, Collada
Softwares Microsoft Visual 200x, Unity3D, Matlab, Eclipse, Delmia, CATIA, Mitsuba, Povray, 3DSMax, Qualisys, Motive, Optitrack and Visual 3d

Research Works and Projects

Time series analysis (2017 - ) Classification, Feature selection (Gaussian process regression, HMM, DTW, Random forest)
Feature selection from similiraties on multiple time series

What are the common spatio-temporal features between the different gestures performed by expert sport players. Traditionally, research on time series focus on (1) feature selection or feature extraction for classification, (2) on similarities between two time series either on the whole movement (structure-based representation) or on part of movement (shape-based representation), (3) computation of time series linear or non linear correlations. The main issues addressed here focus on (1) time series matching, (2) local similarity selections.

Human vs Artificial intelligence for evaluation and judgement of movements

Action Anticipation: where does the expert focus ? On what the AI relies on ? Many studies deal with where experts focus their gazes to anticipate the aims of opponents. It is for example the case in soccer with the penaly kick or in tennis with the service. We analyse here the differences between the character limbs focused by experts and the features extracted by AI.

Judgement of movements. One way to analyse the quality of a movement is to compare it with the movement of an expert. One of the key issue concerns the non adequation between the computer science results and the human ones. Experts rely on subjective information as biomechanical information or "harmony of the movement". The addressed issues here concern (1) the quantification of the subjective part in the human judgement and (2) the implementation of AIs able to reproduce the human judgements.

Assessment and learning/training of sensory-motor / motor skills in virtual reality (2014 - ) HMI, VR, HMM, DTW, Biomechanics, Gaussian process regression, Computer graphics and animation, Cognition, Sport performance, Virtual opponent, Inferential statistics, Control motor, motion analysis, Sport performance
Using virtual reality to analyse and learn reaction time during the slapshot

The spatio-temporal relationship during the progress of the slapshot action between the shooter and the goalkeeper is very close. A few ms of delay on the part of one or the other can change the outcome of the action. One of the advantage given by VR is to control one virtual opponent to interact with the sport player. We propose here a real time VR simulator able to analyse and give a learning to improve sensory-motor skills of a hockey player.

Penalty kick simulator

Penalty kick simulator designed to 1. assess the penalty scoring abilities of young and adult confirmed players, and 2. improve their performance using personalized training based on an optimization algorithm. The movements and the dive of the virtual goalkeeper are based on the movements of the kicker during the run-up to the ball. The difficulty of the task is constantly adapting to the performance and progress of each individual player. The movements / animation of the virtual goalkeeper are based on the real, motion-captured movements of a professional goalkeeper.

Online Controlled Feedback for Motor Learning in Virtual Reality

Virtual reality allows to offer very specific stimuli such as augmented feedback in real time and in interaction with the participant. The topic deals with a new learning model based on HMMs generating a virtual display of the superimposition of oneself (self-modeling) with a virtual expert (expert-modeling). The contribution concerns the participant's self-control of the time dimension in the visualization of the feedback. It is the learner who chooses the speed and the progression of the feedback via his movement. Our model is rigorously validated by a statistical validation and an experiment concerning the mawashi-geri in karate.

Expert Following Feedback for Motor Learning in Virtual Reality

The main goal of this study was to assess the use of superimposition of self and expert avatars for motor control skill learning with partial movement. Regarding the contrasted methods and results obtained by previous studies in VR, this study allows to confirm the advantages of using this type of feedback. Most of previous studies in VR assessed this feedback on complex movement evolving the whole body, sometimes with large moves (as for example with dance). Moreover, few studies allow highlighting the advantage of this feedback in comparison with research in self and expert modeling.

3D Feedback for Motor Learning: Application to the Roundoff in Gymnastics

The objectives of this study are (1) to assess the use of feedback in 3D (in comparison with video feedback) for motor learning specifically on expert movement reproduction, and (2) to compare the different methods of evaluation used by human science movement (judges evaluation, kinematic features), with the ones proposed by computer animation research areas (dynamic time warping).

Analysis of human judgement and perceptual strategies (2013 - ) Eye tracking, Gaze pattern, Eye tracking data vizualisation, perceptual skills, decision making
[DATA VISUALISATION] Skeleton-based approach to analyzing oculomotor behavior when viewing animated characters

Knowing what people look at and understanding how they analyze the dynamic gestures of their peers is an exciting challenge. In this context, we propose a new approach to quantifying and visualizing the oculomotor behavior of viewers watching the movements of animated characters in dynamic sequences. Using this approach, we were able to illustrate, on a 'heat mesh',the gaze distribution of one or several viewers, i.e.,the time spent on each part of the body, and to visualize viewers' timelines,which are linked to the heat mesh. Our approach notablyprovidesan 'intuitive' overview combining the spatial and temporal characteristics of the gaze pattern, thereby constituting an efficient tool forquickly comparing the oculomotor behaviors of different viewers. The functionalities of our system are illustrated through two use case experiments with 2D and 3D animated media sources, respectively validated by a statistical validation and an experiment concerning the penalty in soccer.

ETVIS 2016 JEMR 2017
Motion Analysis, edition and synthesis (2010 - ) Representation of the movement using relationships, Laplacian operator, metric space, classification
Skeletal mesh animation driven by few positional constraints

The challenge proposed by this study is to reconsider the entire animation pipeline for data-driven character animation. By observing that significant loss of information and precision occur in the traditional animation pipeline (skeleton reconstruction from markers, rigging and retargeting), our goal is to directly control at interactive framerates articulated meshes from a low number of positional constraints. Our method builds on top of efficient deformation techniques and proceeds as follows: an original mesh is embedded into a coarse volumetric control lattice which contains simplified information from the initial reference mesh, skeleton elements and marker locations. An iterative method is applied on this structure which preserves the geometry details, the bones lengths, and the associated joint limits. We show the ability of our approach to animate and interactively deform high resolution models from a low-number of markers while retaining the subtleties of the motion. It notably allows to entirely skip the tedious rigging phase

Reconstruction de trajectoires de marqueurs issues de la capture de mouvement

Use of the discrete Laplacian operator to reconstruct the missing marker position data. Each posture of the motion is described by a graph whose vertices are characterized by differential information and some edges are associated with distance constraints. Differential information is used to preserve the spatial relationships between markers while distance constraints enable to preserve the length of some edges.

THESE: Utilisation des relations spatiales pour l'analyse et l'édition de mouvement

In this document, we propose to study other representations of the motion through a set of spatial relationships. Thus, we propose two approaches~: the first one considers the motion in the metric space and the second one characterizes each posture by a differential representation using the discrete Laplacian operator.

Spatio-temporal coupling with the 3D+t motion Laplacian

Representation of the motion based on the Laplacian expression of a 3D+t graph: the set of connected graphs given by the skeleton over time. Through this Laplacian representation of the motion, we propose an application which allows an easy and interactive editing, correction or retargeting of a motion.

Motion Retrieval in the Metric Space

This project advocates the idea that the metric space (i.e. set of joint-to-joint distances of the skeleton), though bigger, can yield a powerful representation of the motion. In order to validate this idea, comparisons with rotation and position based representations are experimented in a motion retrieval task performed with the HDM05 motion database. The final resulting retrieval algorithm is very fast with satisfying performances.

Cinématique guidée par les distances

This study proposes a general method for driving kinematics by distances and more specifically for controlling kinematically articulated systems. Unlike traditional approaches, the problem is addressed in the metric space using distances belonging to points of the skeleton and to the environment. After defining kinematic control through a distance-based formalization, we propose an optimization method for solving classic issues such as motion adaptation and inverse kinematics. The originality of the method lies in the possibility to introduce distance constraints with priorities. The approach is validated by a large variety of experiments in the field of motion control of articulated figures, and compared to other approaches by means of stability, convergence and performance issues.

HMI for Interactive Virtual Signers (2008 - 2010) Synthesis of Natural Language Processing — Language generation; Three-Dimensional Graphics and Realism—Animation

System for Data-Driven Animation of Interactive Virtual Signers:

In this paper we present a multichannel animation system for producing utterances signed in French Sign Language (LSF) by a virtual character. The main challenges of such a system are simultaneously capturing data for the entire body, including the movements of the torso, hands, and face, and developing a data-driven animation engine that takes into account the expressive characteristics of signed languages. Our approach consists of decomposing motion along different channels, representing the body parts that correspond to the linguistic components of signed languages. We show the ability of this animation system to create novel utterances in LSF, and present an evaluation by target users which highlights the importance of the respective body parts in the production of signs. We validate our framework by testing the believability and intelligibility of our virtual signer.

IVA/GALA 2009: TIIS 2011:

Other projects

Analyse des flux humains sur la course Sierre-Zinal Crowd simulation, Time prediction

Face à l'engouement (plusieurs milliers de participants) pour cette mythique course valaisanne, la question des ralentissements dans certaines portions étroites vient la problématique de la gestion des flux humain. Nous avons développé un simulateur de foule appliqué au parcours de Sierre-Zinal (longueur, dénivelé, largeur des chemins) et l’avons appliqué à quelques 5000 agents répartis selon des caractéristiques de performance représentative de la population amateur. Suite aux résultats concluants (quelques minutes d’erreur, 10mn par participant), les organisateurs ont modifié la configuration de la course.

Implemented in C++ -- Projet réalisé avec Guillaume Maire et Valentin Genoud.


> Soumissions en cours
Control your Virtual Teacher: Concurrent Self-Paced Feedback for Motor Learning in Virtual Reality, Thibaut Le Naour, Thomas Dévaud and Jean-Pierre Bresciani, Submitted to the journal Transactions on Visualization and Computer Graphics -- 2019
> Revues internationales
Human-Avatar Interaction in Virtual Reality to Assess and Train Sensorimotor Skills: Application to the Slapshot in Hockey, Thibaut Le Naour, Ludovic Hayoz and Jean-Pierre Bresciani, Journal of Virtual Reality -- 2020
Superimposing 3D Self + Expert Modeling in Virtual Reality for Motor Learning: Application to the Throw in American Football, Thibaut Le Naour, Ludovic Hamon and Jean-Pierre Bresciani, Frontiers in Information and Communication Technology (ICT) - Virtual Environments (journal) -- 2019
Kinematics in the Metric Space, Thibaut Le Naour, Nicolas Courty and Sylvie Gibet, Computer and Graphics -- 2019
3D Feedback for Motor Learning: Application to the Roundoff Movement in Gymnastics, Thibaut Le Naour, Chiara Ré and Jean-Pierre Bresciani, Human Movement Science journal -- 2019
Skeletal mesh animation driven by few positional constraints , Thibaut Le Naour, Nicolas Courty and Sylvie Gibet, Computer Animation and Virtual Worlds -- 2019
A skeleton-based approach to analyzing oculomotor behavior when viewing animated characters, Thibaut Le Naour and Jean-Pierre Bresciani, Journal of Eye Movement Research -- 2017
Spatiotemporal coupling with the 3d+ t motion laplacian, Thibaut Le Naour, Nicolas Courty and Sylvie Gibet, Computer Animation and Virtual Worlds -- 2013
The SignCom system for data-driven animation of interactive virtual signers: Methodology and Evaluation, Sylvie Gibet, Nicolas Courty, Kyle Duarte and Thibaut Le Naour , ACM Transactions on Interactive Intelligent Systems (TiiS) -- 2011
> Revues nationales
Utilisation des relations spatiales pour la reconstruction de trajectoires de marqueur issues de la capture de mouvement, Thibaut Le Naour, Nicolas Courty, Sylvie Gibet, Revue Electronique Francophone d'Informatique Graphique (REFIG) -- 2015
Cinématique guidée par les distances, Thibaut Le Naour, Nicolas Courty, Sylvie Gibet, Revue Electronique Francophone d'Informatique Graphique (REFIG) -- 2012
> Conférences internationales
Skeletal Mesh Animation Driven by Few Positional Constraints, Thibaut Le Naour, Nicolas Courty, Sylvie Gibet , Computer Animation and Social Agent (CASA) -- Paris (France) -- Best paper award -- 2019
A Skeleton-based Approach to Analyze Occulomotor Behavior when Viewing Animated Characters, Thibaut Le Naour, Jean-Pierre Bresciani, Eye Tracking and Visualization (ETVIS) -- Baltimore (USA)-- 2016
Spatio-temporal coupling with the 3D+t motion Laplacian, Thibaut Le Naour, Nicolas Courty, Sylvie Gibet, Computer Animation and Social Agent (CASA) -- Istanbul (Turkey) -- 2013
A combined semantic and motion capture database for real-time sign language synthesis, Charly Awad, Nicolas Courty, Kyle Duarte, Thibaut Le Naour, Sylvie Gibet, nternational Workshop on Intelligent Virtual Agents (IVA2009) -- 2009
Gérard: Interacting with Users of French Sign Language, Charly. Awad, Kyle. Duarte, T. Le Naour, GALA 09 (AFIG) -- 2009
> Conférences nationales
Utilisation des relations spatiales pour la reconstruction de trajectoires de marqueur issues de la capture de mouvement, Thibaut Le Naour, Nicolas Courty, Sylvie Gibet, Association Française d'Informatique Graphique (AFIG) -- 2013
Cinématique guidée par les distances, Thibaut Le Naour, Nicolas Courty, Sylvie Gibet, Association Française d'Informatique Graphique (AFIG) -- 2011
Constitution d'une base de données de gestes de la langue des signes françaises - projet SignCom, Duliscouet, Laouen, Franck Multon, Xiubo Liang, Sylvie Gibet, Kyle Duarte, Thibaut Le Naour, Nicolas Courty, Patrice Dalle, Juliette Dalle, Florian Nouviale, Stéphane Donikian, Jérôme Foucher, and Julia Pelhate, AIn Proceedings of the Colloque A3DM 2010 -- 2010
> Conférences / Communications sans actes / Invited Talks
A penalty kick simulator based on human-avatar interaction , Thibaut Le Naour, Jean-Pierre Bresciani , Fribourg Day of Cognition 2016 - 2016
Using Spatial Relationships for tracking, edition and synthesis of movement, Thibaut Le Naour, Invited Talk (Coplab, Fribourg) -- 2014
Indexation et Recherche de mouvements via l'Espace Métrique, Thibaut Le Naour, Nicolas Courty, Sylvie Gibet, journée des doctorants de l’école doctorale Santé, Information, Communication, Matière et Mathématiques (SICMA 2012) -- 2012


Medicine Section,
Dpt. of Neuroscience,
University of Fribourg,
Bd. de Pérolles 90 – Office D340,
CH-1700 Fribourg/Freiburg
+41 (0)26 300 83 07

Thibaut Le Naour @ All Rights Reserved 2020