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Electrical and Computer Enginnering Department
University of Patras

Skodras Evangelos

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PhD Researcher
Artificial Intelligence Group
Wire Communications Laboratory
Electrical and Computer Engineering Dept.
University of Patras

Contact Details

2610 969 806

Wire Communications Laboratory
Department of Electrical and Computer Engineering
University of Patras
GR - 26 500, Rion, Patras, Greece




Evangelos Skodras was born in Patras in 1985. He received his degree in Electrical and Computer Engineering from the University of Patras, Greece, in 2009. He is currently working towards his PhD at the Wire Communications Laboratory. In Aprill 2011 he worked for a three month period as a visiting PhD researcher in the Multimedia Signal Processing Group at EPFL, Lausanne, Switzerland. His research interests are in the area of computer vision and include eye localization, gaze tracking, machine learning, object detection and tracking.


Research Interests: 
Computer Vision
Image and Video Processing
Human Computer Interaction
Facial Features Detection
Object Recognition
Object Tracking
Skodras E. Fakotakis N., “Precise Localization of Eye Centers in Low Resolution Color Images”, Image and Vision Computing Journal, Elsevier, 2015.

Skodras E., Kanas V. and Fakotakis N., “On Visual Gaze Tracking Based on a Single Low Cost Camera”, Signal Processing: Image Communication, Elsevier. (in press)

Lebreton P., Skodras E., Mäki T., Hupont I., Hirth M., "Bridging the gap between eye tracking and crowdsourcing", SPIE Conference on Human Vision and Electronic Imaging XX, San Francisco, California, USA, Feb 2015.

Hupont I., Lebreton P., Mäki  T., Skodras E., Hirth M., "Is affective crowdsourcing reliable?”, 5th IEEE International Conference on Communications and Electronics, Vietnam, 2014.

Yazdani A., Skodras E., Fakotakis N. and Ebrahimi T.,"Multimedia Content Analysis for Emotional Characterization of Music Video Clips",  EURASIP Journal on Image and Video Processing, 2013.

Skodras E.Fakotakis N."An Accurate Eye Center Localization Method for Low Resolution Color Imagery", International Conference on Tools with Artificial Intelligence (ICTAI 2012), Athens, Greece, November 7-9, 2012BibTex  Paper  Presentation  Video

Skodras E.
Siogkas G.Dermatas E., and Fakotakis N."Rear Lights Vehicle Detection for Collision Avoidance", International Conference on Systems, Signals and Image Processing (IWSSIP 2012), Vienna, Austria, 04/2012. BibTex  Paper  Presentation  Video

Siogkas G.
Skodras E., and Dermatas E."Traffic Lights Detection in Adverse Conditions Using Color, Symmetry and Spatiotemporal Information", International Conference on Computer Vision Theory and Applications (VISAPP 2012), Rome, Italy, 02/2012.

BibTex  Paper 

Skodras E.
, and Fakotakis N."An unconstrained method for lip detection in color images", Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, pp. 1013 -1016, 05/2011.  BibTex  Paper  Poster

  Publications in Greek:

Σκόδρας Ε., Σιόγκας Γ., Δερματάς Ε., "Αναγνώριση Προπορευόμενου Οχήματος με Ψηφιακή Επεξεργασία Εικόνας", 3ο Πανελλήνιο Επιστημονικό Φοιτητικό Συνέδριο Πληροφορικής ("Φοιτητικό ΕΥΡΗΚΑ" 2009), Κέρκυρα, 10-12 Σεπτεμβρίου 2009 Paper





Awards and Prizes: 

  • Most  Innovative  App  prize for “Eye Type” mobile application -  EESTEC  International  Android  Competition 2015 
  • Computer Society Award  for “Eye Type” mobile application - IEEE Mobile Application Development Contest 2015  
  • Best Paper Award  - 3rd Panhellenic Student Conference, Eureka 2009, Corfu, Greece, 10-12 Sep. 2009
Membership of Societies and Professional Bodies: 

Demo Videos

Demo videos of Eye Loc and Eye Type. Eye Loc is an Android mobile application which localizes the eye centers of a person the camera is capturing, in real time. The Eye Type application allows users to input text to a mobile device, using only the movement of their eyes.

Demo videos of the methods described in "An Accurate Eye Center Localization Method for Low Resolution Color Imagery" and "Rear Lights Vehicle Detection for Collision Avoidance", respectively. The databases used 
 are a publicly available image sequence of driving in an urban environment, available at and a driver monitoring image sequence which can be made available by request at (4512 frames + Ground Truth of eye centers).