Image preprocessing techniques for facial expression classification

  • Andre Luiz da S. Pereira UFF
  • Leandro A. F. Fernandes UFF
  • Aura Conci UFF

Abstract


Facial expression classification is an essential aspect of human interaction, and its proper classification is considered fundamental for the future inclusion of multimedia psychology into human-computer interfaces. For this purpose, this article aims to identify a preprocessing pipeline capable of reduce the accuracy variance for facial expression classification. Thereunto, Extended Cohn-Kanade Dataset, Support Vector Machine, and Bag of Features were used in six pipelines. Compared to a pipeline with minimal preprocessing, the best results presented an accuracy variance reduction of 65.63%.

Keywords: Facial expression, Image processing, Support Vector Machine, Feature computation, Bag of features

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Published
2022-06-22
PEREIRA, Andre Luiz da S.; FERNANDES, Leandro A. F.; CONCI, Aura. Image preprocessing techniques for facial expression classification. In: LIFE IMPROVEMENT IN QUALITY BY UBIQUITOUS EXPERIENCES WORKSHOP (LIQUE), 2. , 2022, Aveiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 5-8. DOI: https://doi.org/10.5753/lique.2022.19995.