Emotion recognition algorithm based on linear regression

Kovalyova Elena Sergeevna

Emotion recognition algorithm based on linear regression

Kovalyova E. S.

Kovalyova Elena Sergeevna

graduate student, Lomonosov Moscow State University, Faculty of Mechanics and Mathematics, Chair of Mathematical Theory of Intellectual Systems

Published: 2024, vol. 28, issue 1, pp. 48–59

Download full text (In Russian)

Abstract

The paper proposes a method for recognizing emotions in facial images using linear regression using two neural networks (MediaPipe[1] and Dlib[2]), which locate key points in images of people’s faces. This article will show: creating a database for the training set, features that will be used to train the classiﬁer, building a linear classiﬁer and the result of its work on the training set. The goal of the work is to identify key features at key points by which one or another emotion can be recognized. The proposed approaches may be useful, in particular, when training multilayer neural networks, the training of which will improve the quality of recognition of emotions in images.

Keywords: keypoint, MediaPipe, Dlib, linear classifier.

BibTeX

@article{IS-Kovalyova2024,
  author  = {Kovalyova, Elena Sergeevna},
  title   = {{Emotion recognition algorithm based on linear regression}},
  journal = {Intelligent Systems. Theory and Applications},
  year    = {2024},
  volume  = {28},
  number  = {1},
  pages   = {48--59},
}

AMSBIB

\Bibitem{IS-Kovalyova2024}
\by E.\,S.~Kovalyova
\paper Emotion recognition algorithm based on linear regression
\jour Intelligent Systems. Theory and Applications
\yr 2024
\vol 28
\issue 1
\pages 48--59
\lang In Russian

Published under Creative Commons Attribution 4.0 International (CC BY 4.0)

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