Michel Valstar

Contact

• workRoom B79 School of Computer Science
  Jubilee Campus
  Wollaton Road
  Nottingham
  NG8 1BB
  UK
• workn/a
• Michel.Valstar@nottingham.ac.uk
• https://www.cs.nott.ac.uk/~pszmv

Teaching Summary

I am teaching G53MLE, a level-3 module on Machine Learning, as well as G53SEC, a level-3 module on computer and network security.

Currently I'm supervising the following students:

• Timur Almaev
• Andry Chowanda
• Shashank Jaiswal
• Haris Khan
• Kirsty Smith
• Xiaomeng Wang
• Chao Zhang: 'Automatic Semantic Tagging of Surveillance Video Streams for Important Event Prediction and Detection'

I'm also co-supervising Bihan Jiang at Imperial College; who's first supervisor is Prof. Maja Pantic.

Research Summary

Michel Valstar is a researcher in Automatic Visual Understanding of Human Behaviour. This encompasses Machine Learning, Computer Vision, and a good idea of how people behave in this world.

He studies the relation between medical conditions and expressive behaviour, and what role affective computing and social signal processing can have to help diagnose, monitor, or treat these conditions. (Behaviomedics).

Recent Publications

• ENRIQUE SANCHEZ LOZANO, BRAIS MARTINEZ, YORGOS TZIMIROPOULOS and MICHEL VALSTAR, 2016. Cascaded Continuous Regression for Real-time Incremental Face Tracking In: Proc. European Conference on Computer Vision (ECCV2016).
• MARTINEZ, BRAIS and VALSTAR, MICHEL F, 2016. L 2, 1-based regression and prediction accumulation across views for robust facial landmark detection Image and Vision Computing. 47, 36-44
• X. WANG, M. VALSTAR, B. MARTINEZ, M. H. KHAN and T. PRIDMORE, 2015. TRIC-track: Tracking by Regression with Incrementally Learned Cascades In: 2015 IEEE International Conference on Computer Vision (ICCV). 4337-4345
• ALMAEV, TIMUR, MARTINEZ, BRAIS and VALSTAR, MICHEL, 2015. Learning to transfer: transferring latent task structures and its application to person-specific facial action unit detection In: Proceedings of the IEEE International Conference on Computer Vision. 3774-3782

• View all publications

• ENRIQUE SANCHEZ LOZANO, BRAIS MARTINEZ, YORGOS TZIMIROPOULOS and MICHEL VALSTAR, 2016. Cascaded Continuous Regression for Real-time Incremental Face Tracking In: Proc. European Conference on Computer Vision (ECCV2016).
• MARTINEZ, BRAIS and VALSTAR, MICHEL F, 2016. L 2, 1-based regression and prediction accumulation across views for robust facial landmark detection Image and Vision Computing. 47, 36-44
• X. WANG, M. VALSTAR, B. MARTINEZ, M. H. KHAN and T. PRIDMORE, 2015. TRIC-track: Tracking by Regression with Incrementally Learned Cascades In: 2015 IEEE International Conference on Computer Vision (ICCV). 4337-4345
• ALMAEV, TIMUR, MARTINEZ, BRAIS and VALSTAR, MICHEL, 2015. Learning to transfer: transferring latent task structures and its application to person-specific facial action unit detection In: Proceedings of the IEEE International Conference on Computer Vision. 3774-3782
• WANG, XIAOMENG, VALSTAR, MICHEL, MARTINEZ, BRAIS, HARIS KHAN, MUHAMMAD and PRIDMORE, TONY, 2015. Tric-track: Tracking by regression with incrementally learned cascades In: Proceedings of the IEEE International Conference on Computer Vision. 4337-4345
• MARTINEZ, B., VALSTAR, M.F., BINEFA, X. and PANTI, M., 2013. Local evidence aggregation for regression based facial point detection IEEE Transactions on Pattern Analysis and Machine Intelligence. 35(5), 1149-1163
• VALSTAR, M.F. and PANTIC, M., 2012. Fully automatic recognition of the temporal phases of facial actions IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics. 42(1), 28-43
• VALSTAR, M., MEHU, M., JIANG, B., PANTIC, M. and SCHERER, K., 2012. Meta-analysis of the first facial expression recognition challenge IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. 42(4), 966-979
• SCHROEDER, M., BEVACQUA, E., COWIE, R., EYBEN, F., GUNES, H., HEYLEN, D., MAAT, M., MCKEOWN, G., PAMMI, S., PANTIC, M., PELACHAUD, C., SCHULLER, B., DE SEVIN, E., VALSTAR, M. and WÖLLMER, M., 2011. Building autonomous sensitive artificial listeners IEEE Transactions on Affective Computing. 3(2), 165-183
• GARY MCKEOWN, MICHEL VALSTAR, RODDY COWIE, MAJA PANTIC and MARC SCHROEDER, 2011. The SEMAINE database: annotated multimodal records of emotionally coloured conversations between a person and a limited agent Transactions on Affective Computing. 99(1), 1
• VALSTAR, M., JIANG, B., MEHU, M., PANTIC, M. and SCHERER, K., 2011. The first facial expression recognition and analysis challenge In: IEEE International Conference on Automatic Face and Gesture Recognition. 921-926
• JIANG, B., VALSTAR, M.F. and PANTIC, M., 2011. Action unit detection using sparse appearance descriptors in space-time video volumes In: Automatic Face & Gesture Recognition and Workshops (FG20122), San Diego, USA. 314-321
• VALSTAR, M., MARTINEZ, B., BINEFA, X. and PANTIC, M., 2010. Facial point detection using boosted regression and graph models In: 2010 IEEE Conference on Computer Vision and Pattern Recognition. 2729-2736
• ROBINSON EC, VALSTAR M, HAMMERS A, ERICSSON A, EDWARDS AD and RUECKERT D, 2008. Multivariate Statistical Analysis Of Whole Brain Structural Networks Obtained Using Probabilistic Tractography. Medical Image Computing And Computer-Assisted Intervention : Miccai ... International Conference On Medical Image Computing And Computer-Assisted Intervention. 11(Pt 1), 486-93
• VALSTAR, MF, GUNES, H and PANTIC, M, 2007. How To Distinguish Posed From Spontaneous Smiles Using Geometric Features