TCTS Lab Staff

Sohaib Laraba

[Bio] [Research] [Related Projects] [Publications]

Researcher, PhD student  

University of Mons (UMONS) 
Engineering Faculty of Mons (FPMs) 

Numediart Research Institute  
TCTS Lab  
31, Boulevard Dolez  
B-7000 Mons (Belgium)  

phone: +32 65 37 47 21  
fax: +32 65 374729  

LinkedIn profile Researchgate profile Scholar profile
I hold an Electronics Engineering degree from the National Polytechnic School of Algiers (ENP) and a Master degree in Signal, Image, Speech and Telecom from the National Polytechnic Institute of Grenoble (INPG | Phelma) in France.

Currently, I'm a PhD student at the TCTS lab of the University of Mons (UMONS) and my research includes stylistic gestures analysis and recognition using different motion capture systems and exploring high level motion features that describe the most the gestures, in addition to Human-Machine interactions.

Also, I'm a research assistant at Umons and I work on the European project i-Treasures. I work on the Analysis of a traditional dance from the Walloon region (south) of Belgium using different motion capture technologies. My mission is to contact experts in order to select important aspects of this dance and develop algorithms for recognition and evaluation of dancers. I also organize meetings with different partners in Europe, write quarterly and annual reports about advances of the work and for collaboration purposes in addition to presentations, demos and workshops to present the work to public.

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Title: Real-time Motion Recognition and Motion Quality Assessment:

Abstract: The work in this thesis consists on the conception, realization and validation of a real-time motion recognition methodology, based on skeleton tracking data, taking into account the recognition or characterization of the motion « quality » or motion « style ».
This work contributes towards development of virtual training systems based on machine learning and efficient feature extraction methods. It includes also techniques of model adaptation for sensor-to-sensor gesture recognition and evaluation.

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Related Projects:


i-Treasures (Intangible Treasures - Capturing the Intangible Cultural Heritage and Learning the Rare Know-How of Living Human Treasures FP7-ICT-2011-9-600676-i-Treasures) is an Integrated Project (IP) of the European Union's 7th Framework Programme 'ICT for Access to Cultural Resources'. The project started on February 1, 2013, and will last 48 months.

The main objective of i-Treasures is to develop an open and extendable platform to provide access to ICH resources, enable knowledge exchange between researchers and contribute to the transmission of rare know-how from Living Human Treasures to apprentices. To this end, the project aims to go beyond the mere digitization of cultural content. Its main contribution is the creation of new knowledge by proposing novel methodologies and new technological paradigms for the analysis and modeling of Intangible Cultural Heritage (ICH). One of the main objectives of the proposal is the development of an appropriate methodology based on multisensory technology for the creation of information (intangible treasures) that has never been analyzed or studied before.

Within the i-Treasures project, the usability of the platform will be demonstrated in four different case studies: a) Rare Traditional Songs, b) Rare Dance Interactions, c) Traditional Craftsmanship and d) Contemporary Music Composition.

MotionMachine framework

MotionMachine is a C++ software toolkit for rapid prototyping of motion feature extraction and motion-based interaction design. It encapsulates the complexity of motion capture data processing into an intuitive and easy-to-use set of APIs, associated with the openFrameworks environment for visualisation. MotionMachine is a new framework designed for “sense-making”, i.e. enabling the exploration of motion-related data so as to develop new kinds of analysis pipelines and/or interactive applications.

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Publications :

Regular Papers in Journals

S. LARABA, M. BRAHIMI, J. TILMANNE, T. DUTOIT. 2017, "3D Skeleton-Based Action Recognition by Representing Motion Capture Sequences as 2D-RGB Images", Computer Animation and Virtual Worlds (CAVW), 2017.

S. LARABA, J. TILMANNE, 2016, "Dance performance evaluation using hidden Markov models", Computer Animation and Virtual Worlds (CAVW), 2016. doi:10.1002/cav.1715.

Papers in Conference Proceedings

T. Ravet, J. TILMANNE, N. d’Alessandro and S. Laraba, 2016, "Motion Data and Machine Learning: Prototyping and Evaluation", Human Centered Machine Learning at CHI, 2016.

S. LARABA, J. TILMANNE, T. DUTOIT, 2016, "The i-Treasures Intangible Cultural Heritage Dataset", Proceedings of the 3rd International Symposium on Movement and Computing (MOCO), 2016. doi:10.1145/2948910.2948944.

S. LARABA, J. TILMANNE, T. DUTOIT, 2016, "Adaptation Procedure for HMM-Based Sensor-Dependent Gesture Recognition", Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games (MIG), 2015. ACM, 2015, pp. 17-22. doi:10.1145/2822013.2822032.

J. Tilmanne, N. d'Alessandro, P. Barborka, F. Bayansar, F. Bernardo, R. Fiebrink, A. Heloir, E. Hemery, S. Laraba, A. Moinet, F. Nunnari, T. Ravet, L. Reboursière, A. Sarasua, M. Tits, N. Tits, and F. Zajéga, 2015, "Prototyping a New Audio-Visual Instrument Based on Extraction of High-Level Features on Full-Body Motion", Proceedings of the 10th International Summer Workshop on Multimodal Interfaces (eNTERFACE). Mons, Belgium, August 2015.

Technical Reports

M. Tits, S. LARABA, J. TILMANNE, D. Ververidis, S. Nikolopoulos, S. Nikolaidis, A. P. Chalikias, 2016, "Intangible Cultural Heritage Indexing by Stylistic Factors and Locality Variations - FP7 i-Treasures Deliverable 4.5. 2016.

B. Denby, C. Leboullenger, P. Roussel, A. Manitsaris, A. Katos, A. Glushkova, G. Nikos, J. TILMANNE, S. LARABA, V. Christina, K. Dimitropoulos, F. Tsalakanidou, A. Kitsikidis, P. Chawah, S. Dupont, L. Hadjileontiadis, G. D. Sergiadis, S. Manitsaris, 2016, "Final Report on ICH Capture and Analysis - FP7 i-Treasures Deliverable 3.3. January 2016.

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