Selective generation of Gabor features for fast face recognition on mobile devices

  • Authors:
  • Jiyong Oh;Sang-Il Choi;Chunghoon Kim;Jungchan Cho;Chong-Ho Choi

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2013

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Abstract

In this paper, we propose a robust face recognition method to provide fast response on a mobile device by selectively generating Gabor features. The Gabor filter has been popularly used in face recognition to improve recognition performance. Since the computational effort for generating a Gabor feature is very large, it is important to use only the discriminative Gabor features on mobile devices which do not have sufficient computing power. At the same time, it is also important to maintain the recognition performance at an acceptable level. To reduce computational effort without degrading the recognition performance, the proposed method selectively generates Gabor features based on a contribution measure obtained by discriminant analysis. Face recognition is performed using only the selectively generated Gabor features, and the experimental results for the CMU Multi-PIE database and a real world data set show that the number of Gabor features can be reduced by more than 50% while keeping almost the same recognition performance. On a 624MHz mobile phone, the execution time of feature extraction can be reduced to 19ms from 46ms on average.