Principal Directions of Synthetic Exact Filters for Robust Real-Time Eye Localization

  • Vitomir Štruc
  • Jerneja Žganec Gros
  • Nikola Pavešić
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6583)


The alignment of the facial region with a predefined canonical form is one of the most crucial steps in a face recognition system. Most of the existing alignment techniques rely on the position of the eyes and, hence, require an efficient and reliable eye localization procedure. In this paper we propose a novel technique for this purpose, which exploits a new class of correlation filters called Prinicpal directions of Synthetic Exact Filters (PSEFs). The proposed filters represent a generalization of the recently proposed Average of Synthetic Exact Filters (ASEFs) and exhibit desirable properties, such as relatively short training times, computational simplicity, high localization rates and real time capabilities. We present the theory of PSEF filter construction, elaborate on their characteristics and finally develop an efficient procedure for eye localization using several PSEF filters. We demonstrate the effectiveness of the proposed class of correlation filters for the task of eye localization on facial images from the FERET database and show that for the tested task they outperform the established Haar cascade object detector as well as the ASEF correlation filters.


Biometrics eye localization advanced correlation filters 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Vitomir Štruc
    • 1
    • 2
  • Jerneja Žganec Gros
    • 1
  • Nikola Pavešić
    • 2
  1. 1.Alpineon LtdLjubljanaSlovenia
  2. 2.Faculty of Electrical EngineeringUniversity of LjubljanaLjubljanaSlovenia

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