Imperial College London

STEFANOS ZAFEIRIOU, PhD

Faculty of EngineeringDepartment of Computing

Reader in Machine Learning and Computer Vision
 
 
 
//

Contact

 

+44 (0)20 7594 8461s.zafeiriou Website CV

 
 
//

Location

 

375Huxley BuildingSouth Kensington Campus

//

Summary

 

Overview

My research interest lie in the research areas of statistical machine learning (with emphasis on component analysis and kernel learning) with applications in computer vision and general image/signal analysis. In particular, I design and develop statistical machine learning algorithms taylored for 2D/3D object and face recognition, 2D/3D object tracking, 2D/3D deformable object/face alignment, as well as, automatic human behaviour analysis. I apply such algorithms for analysis of various other signals (e.g., brain signals and graphs).

 

Computer Vision

show research

A recent line of research in computer vision is to apply tools from statistical machine learning in order to solve challenging problems such as object recognition, object tracking, image alignment, human behaviour analysis etc. I work on this line of research on the following topics

(1) Deformable models for face alignment. Construction of deformable models provide an excellent paradigm on how elements of computer vision (i.e., 2D/3D motion models, image warping etc) can be successfully combined with elements of statistical machine learning (component analysis). My work on deformable models is on the design and application robust component analysis and optimization methodologies for building facial deformable models that can work on unconstrained conditions.

(2) Face recognition. Arguably face is the most used object in computer vision due to the numerous applications that involve faces, as well as, since it is a appears in very challenging settings (i.e., it is highly deformable, it has drastic appearance changes due to different illumination/poses/aging/cosmetics etc.). My work concentrated on the development of robust algorithms for face recognition in challenging real-world application (e.g., surveillance).  

(3) Human behaviour analysis. Automatic understanding of human behaviour and especially non-verbal facial behaviour from visual input is a key aspect in the majority of modern human computer interaction systems. I am very active in this line of research working towards the design of algorithms that take into account both the spatial, as well as, the temporal (dynamic) nature of human behaviour.    

Statistical Machine Learning

show research

Component analysis, such as Principal Component Analysis, Linear Discriminant analysis, etc is among the most well-researched and popular topics of statistical machine learning. I am working on various aspects of linear/non-linear/multilinear, as well as, probabilistic and deterministic component analysis. My research in component analysis can be divided in the following paths

(1) Defining new component analysis algorithms. One of my main lines of research is the development of  new component analysis for the problems at hand (e.g., incorporating a-priori knowledge etc) and theoretically studying their properties (e.g., convergence)

(2) Robust component analysis. In many cases, due to the similarity measures employed in the definition of the optimization problem which produces the components (i.e., L2 norm etc) component analysis algorithms are very sensitive to noise/outliers. One of my main lines of research is to develop robust component analysis algorithms by designing robust kernels (both positive definite and indefinite).

(3) Probabilistic component analysis is a very powerful framework that naturally allows the incorporation of noise and a-priori knowledge in the developed models. One of my recent lines of my research is to develop a unified framework for probabilistic component analysis.

(3) Complex and hyper-complex valued component analysis. The majority of component analysis have been defined on real-valued data. Very limited research has been conducted on how complex-valued data can be appropriately used in component analysis. The most recent line of my research is the study of component analysis using complex and hyper-complex-valued data.

Current Projects

show research

 

  • EPSRC 4D FAB (4D Facial Behaviour analysis for security applications): 

The main aim of this project is the development of automated tools for automatic spatio-temporal analysis and understanding of human facial behaviour from 4D facial information (i.e. 3D high-quality video recordings of facial behaviour). Two exemplar applications related to security issues will be specifically addressed in this proposal: (a) person verification (i.e. facial behaviour as a form of behaviometrics), and (b) deception indication.

  • Marie Curie International Incoming Fellowship (Facial Expression Recognition in the Wild) of Dr. Akshay Asthana
  • Marie Curie Inter-European Fellowships for Career Development (Automatic Detection of Conflict Escalation and Resolution in Social Interactions) of Mr. Yiannis Panagakis 
  • BBSRC DTP Studentship for Mr. Quentin Geissmann

 

Awards and Prizes

show research
  • One of the best reviewer awards ICCV 2013 (http://www.iccv2013.org/awards.php)
  • Nominated for the prestigious Cor Baayen Award 2008 of the European Research Consortium for Informatics and Mathematics
  • Finalist of the European Biometric Research Award of the European Biometric Forum 2006
  • Award and scholarship for his Phd studies by Aristotle University Research Committee (2005)
  • Scholarship of A. Onassis Foundation for participation in summer school, 2003
  • Scholarship Thomas Papamixailidis, Heritage Committee of Aristotle University of Thessaloniki, 2002-2003
  • Scholarship by the Greek State Scholarships Foundation, 2002.
  • Award by Department of Informatics, Aristotle University of Thessaloniki 2002.
  • Award by Greek Mathematical Society 1999.

Student Fellowships with Proposal Submission

show research

 

  • Intel Fellowship - Mr. Stephan Liwicki
  • Qualcomm Fellowship - Mr. Joan Alabort i Medina
  • Google Fellowship - Mr. Konstantinos Bousmalis
  • Greek State Scholarship Foundation Fellowship - Mr. Athanasios Papaioannou

Editorial Board/ Guest Editorials

show research
  • Associate Editor, IEEE Transactions on Systems Man and Cybernetics B, 2011-2013
  • Associate Editor, IEEE Transactions on Cybernetics  2013-now
  • Associate Editor, Image and Vision Computing Journal, 2011-now 
  • Guest Editor, Multibiometrics/Mobile Biometrics, Image and Vision Computing Journal, 2013
  • Guest Editor, Modern Control for Computer Games, IEEE Transactions on Systems Man and Cybernetics B, 2012
  • Guest Editor, 3D Facial Behaviour Analysis/Understanding, Image and Vision Computing Journal, 2011

POSTDOC/ RESEARCH STAFF SUPERVISION

show research

Current:

  • Research Fellow, Dr. Akshay Asthana 2012-now
  • Research Fellow, Dr. Ioannis Panagakis  2012-now
  • Research Associate, Dr. Symeon Nikitidis 2012-now

 

Past:

  • Research Assistant, Ms Yijia Sun
  • Research Assosiate, Dr. Georgios Tzimiropoulos

PhD Student Supervision

show research
  • Mr. George Trigiorgis (joint with Dr. Bjorn Schuller) 2013-expected 2017
  • Quentin Geissmann (joint with Dr. Giorgio Gilestro) 2013-expected 2017
  • Vahan Hovhannisyan (joint with Dr. Panos Parpas) 2013-expected 2017
  • Shiyang Cheng (joint with Prof. Maja Pantic) 2013 -expected 2016
  • Epameinontas Antonakos 2013-expected 2017
  • James Booth 2013-expected 2017
  • Christos Kampouris 2012-expected 2016
  • Patrick Snape 2012-expected 2016
  • Joan Alabort (Qualcomm Fellowship) 2012-expected 2016
  • Christos Sagonas (joint with Prof. Maja Pantic) 2012-expected 2016
  • Athanasios Papaioannou 2012 -expected 2016
  • Ioannis Marras (joint with Prof. Maja Pantic) 2011 -expected 2014
  • Georgia Sandbach (joint with Prof. Maja Pantic) 2010-expected 2014
  • Stephan Liwicki (Intel Fellowship) (joint with Prof. Maja Pantic) 2010-2014
  • Konstantinos Bousmalis (Google Fellowship) (joint with Prof. Maja Pantic) 2009-2014