Facial Expression Identification using Regularized Supervised Distance Preserving Projection

Authors

  • Sohana Jahan Department of Mathematics, University of Dhaka, Dhaka-1000, Bangladesh
  • Moriyam Akter Department of Mathematics, University of Dhaka, Dhaka-1000, Bangladesh
  • Sifta Yeasmin Department of Mathematics, University of Dhaka, Dhaka-1000, Bangladesh
  • Farhana Ahmed Simi Department of Mathematics, University of Dhaka, Dhaka-1000, Bangladesh

DOI:

https://doi.org/10.3329/dujs.v69i2.56485

Keywords:

Expression Recognition, K-NN, RSDPP.

Abstract

Facial expression recognition is one of the most reliable and a key technology of advanced human-computer interaction with the rapid development of computer vision and artificial intelligence. Nowadays, there has been a growing interest in improving expression recognition techniques. In most of the cases, automatic recognition system’s efficiency depends on the represented facial expression feature. Even the best classifier may fail to achieve a good recognition rate if inadequate features are provided. Therefore, feature extraction is a crucial step of the facial expression recognition process. In this paper, we have used Regularized Supervised Distance Preserving Projection for extracting the best features of the images. Numerical experiment shows that the use of this technique outperforms many of state of art approaches in terms of recognition rate.

Dhaka Univ. J. Sci. 69(2): 70-75, 2021 (July)

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Published

2021-12-01

How to Cite

Jahan, S., Akter, M. ., Yeasmin, S., & Simi, F. A. . (2021). Facial Expression Identification using Regularized Supervised Distance Preserving Projection. Dhaka University Journal of Science, 69(2), 70–75. https://doi.org/10.3329/dujs.v69i2.56485

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Articles