Research

Research skills

  • Statistical data classification and filtering
  • Bayesian restoration and unsupervised learning
  • Markov models (hidden Markov field and chain, Kalman-like filters)
  • Multidimensional and non-Gaussian modeling
  • Object tracking and Image segmentation
  • Non-Gaussian multidimensionnal signal filtering and prediction

PhD and HDR Theses

  • Thesis from Rennes University, defended december 15, 1999. pdf
  • Habilitation à diriger des recherches from Aix-Marseille University, defended April 29, 2008. pdf

Papers in Int. Journals

  1. Z. Bouyahia, H. Haddad, S. Derrode, and W. Pieczynski, Traffic state prediction using conditionally Gaussian observed Markov fuzzy switching model, Journal of Intelligent Transportation Systems, Vol. 0, Number 0, pp. 1-20, 2022. bibtex.
  2. Z. Bouyahia, H. Haddad, S. Derrode, and W. Pieczynski, Toward a Cost-Effective Motorway Traffic State Estimation From Sparse Speed and GPS Data, IEEE Access, Vol. 9, 44631-44646, 2021. pdf. bibtex.
  3. Z. Bouyahia, S. Derrode, and W. Pieczynski, Filtering in Gaussian Linear Systems with Fuzzy Switches, IEEE Trans. on Fuzzy Systems, Vol. 28(8), 1760-1770, 2020. pdf. bibtex.
  4. F. Zheng, S. Derrode and W. Pieczynski, Semi-supervised optimal recursive filtering and smoothing in non-Gaussian Markov switching models, Signal Processing, Vol. 171, p. 107511, 2020. pdf. bibtex.
  5. H. Li, S. Derrode, and W. Pieczynski, Adaptive On-line Lower Limb Locomotion Activity Recognition Using Semi-Markov Model and Single Wearable Inertial Sensor, Sensors, special issue: Sensors for Gait, Posture, and Health Monitoring, Vol. 19(19), 4242, 2019. pdf. bibtex.
  6. H. Li, S. Derrode, and W. Pieczynski, An adaptive and on-line IMU-based locomotion activity classification method using a triplet Markov model, Neurocomputing, Vol. 362, 94-105, 2019. pdf. bibtex.
  7. Q. Ju, R. Chalon, and S. Derrode, Assisted Music Score Reading Using Fixed-Gaze Head Movement: Empirical Experiment and Design Implications, PACM on Human-Computer Interaction Journal, Vol. 3:1, 1-29, 2019. pdf. bibtex.
  8. F. Zheng, S. Derrode, and W. Pieczynski, Parameter Estimation in Switching Markov Systems and Unsupervised Smoothing, IEEE Trans. on Automatic Control, Vol. 64(4), 1761-1767, 2019. pdf. bibtex.
  9. I. Gorynin, S. Derrode, E. Monfrini, and W. Pieczynski, Fast smoothing in switching approximations of non-linear and non-Gaussian models, Computational Statistics and Data Analysis, Vol. 114, 38–46, 2017. pdf. bibtex.
  10. I. Gorynin, S. Derrode, E. Monfrini, and W. Pieczynski, Fast Filtering in Switching Approximations of Non-linear Markov Systems with Applications to Stochastic Volatility, IEEE Trans. on Automatic Control, Vol. 62(2), 853–862, 2017. pdf. bibtex.
  11. S. Derrode and W. Pieczynski, Unsupervised classification using hidden Markov chain with unknown noise copulas and margins, Signal Processing, Vol. 128, 8-17, 2016. pdf. bibtex.
  12. V. Némesin, and S. Derrode, Quality-driven and real-time iris recognition from close-up eye videos, Signal, Image and Video Processing, Vol. 10(1), 153-160, 2016. pdf. bibtex.
  13. V. Némesin, and S. Derrode, Robust partial-learning in linear Gaussian systems, IEEE Trans. on Automatic Control, Vol. 60(9), 2518-2523, 2015. pdf. bibtex.
  14. N. Abassi, D. Benboudjema, S. Derrode and W. Pieczynski, Optimal filter approximations in Conditionally Gaussian Pairwise Markov Switching Models, IEEE Trans. on Automatic Control, Vol. 60(4), 1104-1109, 2015. pdf. bibtex.
  15. N. Abassi, S. Derrode, F. Desbouvries, and W. Pieczynski, Filtrage statistique optimal rapide dans des systèmes linéaires à sauts non stationnaires, Traitement du Signal, Vol. 31 (3-4), 339-361, 2014. pdf. bibtex.
  16. S. Derrode, L. Benyoussef and W. Pieczynski, Subsampling-based HMC parameters estimation with application to large data sets classification, Signal, Image and Video Processing Journal, Vol. 8(5), 873-882, 2014. pdf. bibtex.
  17. S. Derrode and W. Pieczynski, Exact Fast Computation of Optimal Filter in Gaussian Switching Linear Systems, IEEE Signal Processing Letters, Vol. 20(7), 701-704, 2013 (eq. 19 has been corrected w.r.t published version). pdf. bibtex.
  18. S. Derrode, and W. Pieczynski, Unsupervised data classification using pairwise Markov chains with automatic copulas selection, Computational Statistics & Data Analysis, Vol. 63, 81-98, 2013. pdf. bibtex.
  19. V. Némesin, and S. Derrode, Robust blind pairwise Kalman algorithms using QR decompositions, IEEE Trans. Signal Processing, Vol. 61(1), 5-9, 2013. pdf. bibtex.
  20. S. Derrode, and W. Pieczynski, Segmentation d’images par modèle de mélange conjoint non gaussien, Traitement du Signal, Vol. 29 (1-2), 9-28, 2012. pdf. bibtex.
  21. L. Benyoussef, and S. Derrode, Tessella-oriented segmentation and guidelines estimation of ancient mosaic images, J. of Electronic Imaging, Vol. 17(4), 2008. pdf. bibtex.
  22. Z. Bouyahia, L. Benyoussef, and S. Derrode, Change detection in synthetic aperture radar images with a sliding hidden Markov chain model, J. of Applied Remote Sensing, Vol. 2(1), 023526, 2008. pdf. bibtex.
  23. M.-A. Charmi, S. Derrode, and F. Ghorbel, Fourier-based geometric shape prior for snakes, Pattern Recognition Letters, Vol. 29(7), 897-904, 2008. pdf. bibtex.
  24. L. Benyoussef, C. Carincotte, and S. Derrode, Extension of higher-order HMC modeling with application to image segmentation, Digital Signal Processing, Vol. 18(5), 849-860, 2008. pdf. bibtex.
  25. W. Ketchantang, S. Derrode, L. Martin, and S. Bourennane, Pearson-based mixture model for color object tracking, Machine Vision and Applications, Vol. 19 (5-6), 2008, Special issue on video surveillance research in industry and academia. pdf. bibtex.
  26. S. Derrode, and G. Mercier, Unsupervised multiscale oil slick segmentation from SAR image using a vector HMC model, Pattern Recognition, Vol. 40(3), 1135-1147, 2007. pdf. bibtex.
  27. F. Ghorbel, S. Derrode, R. Mezhoud, T. Bannour, and S. Dhabhi, Image reconstruction from a complete set of similarity invariants extracted from complex moments, Pattern Recognition Letters, Vol. 27(12), 1361-1369, 2006. pdf. bibtex.
  28. C. Carincotte, S. Derrode, and S. Bourennane, Unsupervised change detection on SAR images using fuzzy hidden Markov chains, IEEE Trans. on Geoscience and Remote Sensing, Vol. 44(2), 432-441, 2006. pdf. bibtex.
  29. G. Mercier, S. Derrode, and W. Pieczynski, Segmentation multi-échelle de nappes d’hydrocarbure, Traitement du Signal, Vol. 21(4), 329-346, 2004. pdf. bibtex.
  30. S. Derrode, and W. Pieczynski, Unsupervised signal and image segmentation using pairwise Markov chains, IEEE Trans. on Signal Processing, Vol. 52(9), 2477-2489, 2004. pdf. bibtex.
  31. S. Derrode, and F. Ghorbel, Shape analysis and symmetry detection in gray-level objects using the analytical Fourier-Mellin representation, Signal Processing, Vol. 84(1), 25-39, 2004. pdf. bibtex.
  32. S. Derrode, and F. Ghorbel, Robust and efficient Fourier-Mellin transform approximations for invariant grey-level image description and reconstruction, Computer Vision and Image Understanding, Vol. 83(1), 57-78, 2001. pdf. bibtex.
  33. S. Derrode, R. Mezhoud, and F. Ghorbel, Comparaison de deux familles complètes de descripteurs de formes pour l’indexation de bases d’objets 2D à niveaux de gris, Annals of Telecommunications, Vol. 55(3/4), 184-193, 2000. pdf. bibtex.

PhD (co-)supervision

  1. Léo Schneider, Machine-learning-based analysis of Pseudo Mass-Spectrum Images for Targeted Peptides Identification, Ecole Centrale de Lyon, Started February 1st, 2022. Co-supervised with Jérôme lemoine. abstract.
  2. Mathis Beaubriaud, Reporting automatisé de l’état d’avancement d’un chantier à l’aide de la réalité mixte, École Centrale Lyon, funding: thèse CIFRE SPIE. Started February 1st, 2022. Co-supervised with R. Chalon. abstract.
  3. Liqun Liu, Visualization of Spatial and Temporal Road Traffic Data, École Centrale Lyon, funding: China Scholarship Council. Started October 1st, 2018. Co-supervised with R. Vuillemot. Defended November 26th, 2022. abstract.
  4. Haoyu Li, Recent Hidden Markov Models for Lower Limb Locomotion Activity Detection and Recognition using IMU sensors, École Centrale de Lyon, Co-supervised with W. Pieczynski. Funding: China Scholarship Council. Defended December 4th, 2019. abstract.
  5. Qinjie Ju, Gaze tracking for advanced mobile interaction, École Centrale de Lyon, funding: China Scholarship Council. Co-supervised with R. Chalon. Defended April 9th, 2019. abstract.
  6. Fei Zheng, Introducing copulas in recent Markov models with application to non-Gaussian object following in video. École Centrale de Lyon, funding: China Scholarship Council. Defended December 18th, 2017. abstract.
  7. Valérian Némesin, Apprentissage non-supervisé dans les modèles linéaires gaussiens. Application à la biométrie dynamique de l’iris, Université Aix-Marseille, funding: scholarship DGA/CNRS. Defended September 30th, 2014. abstract.
  8. William Ketchantang, Étude d’une nouvelle modalité vidéo pour la reconnaissance biométrique de l’iris, Université Aix-Marseille, funding: scholarship CIFRE (Société ST-MicroElectronics, Rousset). Defended January 29th, 2008. abstract.
  9. Cyril Carincotte, Segmentation markovienne floue d’images. Application en détection de changements entre images radar, Université Paul Cézanne (Aix-Marseille 3), bourse ministérielle. Defended November 14th, 2005. abstract.
  10. Rim Mezhoud, Indexation de bases d’images planes à l’aide d’invariants complets d’images à niveaux de gris, Université de Tunis II. Defended February 11, 2005. abstract.