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Fast and Robust Face Recognition for Incremental Data

  • I. Gede Pasek Suta Wijaya
  • Keiichi Uchimura
  • Gou Koutaki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6469)

Abstract

This paper proposes fast and robust face recognition system for incremental data, which come continuously into the system. Fast and robust mean that the face recognition performs rapidly both of training and querying process and steadily recognize face images, which have large lighting variations. The fast training and querying can be performed by implementing compact face features as dimensional reduction of face image and predictive LDA (PDLDA) as face classifier. The PDLDA performs rapidly the features cluster process because the PDLDA does not require to recalculate the between class scatter, S b , when a new class data is registered into the training data set. In order to get the robust face recognition achievement, we develop the lighting compensation, which works based on neighbor analysis and is integrated to the PDLDA based face recognition.

Keywords

Face Recognition Recognition Rate Face Image Incremental Data Holistic Feature 
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 2011

Authors and Affiliations

  • I. Gede Pasek Suta Wijaya
    • 1
    • 2
  • Keiichi Uchimura
    • 1
  • Gou Koutaki
    • 1
  1. 1.Computer Science and Electrical Engineering of GSSTKumamoto UniversityKumamoto ShiJapan
  2. 2.Electrical Engineering Department, Faculty of EngineeringMataram UniversityWest Nusa TenggaraIndonesia

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