Tracking Facila Expressions by using Stereoscopy Video and Back Propagation Neural Network

Authors

  • R Romero-Herrera Computing Higher School-ESCOM
  • FJ Gallagos-Funes Superior School of Mechanical and Electrical Engineering National Polytechnic Institute, Mexico city
  • AG Juarez-Gracia Superior School of Mechanical and Electrical Engineering National Polytechnic Institute, Mexico city
  • J López-Bonilla Computing Higher School-ESCOM

DOI:

https://doi.org/10.3126/kuset.v6i1.3303

Keywords:

Facial expression, Backpropagation neural networks, VJ method, Nitzberg algorithm

Abstract

In this paper we propose a method to tracking facial expressions. A system with two cameras is used to
capture stereoscopic video sequences. The frames are acquired and analyzed by matching two
stereoscopic frames through a correlation method that performs image processing to obtain a resulting
frame, and then it is processed to recognize a human face by using the Viola and Jones (VJ) method. The
face is located via the Nitzberg operator and it provides the feature points of the eyes, eyebrows, nose
and mouth, which are introduced into a Backpropagation neural network that is capable of learning and
classifying different types of facial expressions that make a person, feel such as: surprised, scared,
unhappy, sad, mad and happy. Finally, the result of this process is recognition of facial expressions.

Keywords: Facial expression; Backpropagation neural networks; VJ method; Nitzberg algorithm.

DOI: 10.3126/kuset.v6i1.3303

Kathmandu University Journal of Science, Engineering and Technology Vol.6(1) 2010, pp11-24

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How to Cite

Romero-Herrera, R., Gallagos-Funes, F., Juarez-Gracia, A., & López-Bonilla, J. (2010). Tracking Facila Expressions by using Stereoscopy Video and Back Propagation Neural Network. Kathmandu University Journal of Science, Engineering and Technology, 6(1), 11–24. https://doi.org/10.3126/kuset.v6i1.3303

Issue

Vol. 6 No. 1 (2010)

Section

Original Research Articles

License

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