3D Morphable Models Application for Expanding Face Database Limited to Single Frontal Face Image Per Person

  • Łukasz Kulasek
  • Andrzej Czyżewski
Part of the Advances in Intelligent and Soft Computing book series (volume 84)


Major problem in real world scenarios is lack of suficient image samples per person in database for successful face recognition. In most cases insuficient number of samples per an individual in database is present. This makes face classification almost impossible for larger number of people. This problem is commonly described as ’one sample problem’. Recent state-of-art in face recognition allows to achieve high accuracy using face images with frontal pose. However, recognizing faces with rotations in depth, increases error rate significantly. In this paper we present a method to expand database using 3D morphable models to reconstruct 3D face from a single frontal image sample. By rotating reconstructed face to different views we create series of novel virtual images with pose variations for every individual in database. This approach can help to decrease error rate from pose variations and resolves ’one sample problem’.


Face Recognition Facial Point Virtual Sample Face Recognition Algorithm FERET Database 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Łukasz Kulasek
    • 1
  • Andrzej Czyżewski
    • 1
  1. 1.Multimedia Systems Departament, Electronics, Informatics and Telecommunications FacultyGdansk University of TechnologyGdańskPoland

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