Facial Expression Analysis in Brazilian Sign Language for Sign Recognition

  • Rúbia Reis Guerra UFMG
  • Tamires Martins Rezende UFMG
  • Frederico Gadelha Guimarães UFMG
  • Sílvia Grasiella Moreira Almeida IFMG


Sign language is one of the main forms of communication used by the deaf community. The language’s smallest unit, a “sign”, comprises a series of intricate manual and facial gestures. As opposed to speech recognition, sign language recognition (SLR) lags behind, presenting a multitude of open challenges because this language is visual-motor. This paper aims to explore two novel approaches in feature extraction of facial expressions in SLR, and to propose the use of Random Forest (RF) in Brazilian SLR as a scalable alternative to Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN). Results show that RF’s performance is at least comparable to SVM’s and k-NN’s, and validate non-manual parameter recognition as a consistent step towards SLR.


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GUERRA, Rúbia Reis; REZENDE, Tamires Martins; GUIMARÃES, Frederico Gadelha; ALMEIDA, Sílvia Grasiella Moreira. Facial Expression Analysis in Brazilian Sign Language for Sign Recognition. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 15. , 2018, São Paulo. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . p. 216-227. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2018.4418.