Estimation of facial expression intensity from a sequence of binary face images

Author

Saha, Chandrani ; Ghosh, Kuntal

Author_Institution

Centre for Dev. of Adv. Comput., Kolkata, India

fYear

2011

fDate

3-5 Nov. 2011

Firstpage

1

Lastpage

6

Abstract

This paper presents a method of estimation of facial expression intensity from a sequence of binary facial images obtained from video. The binarization has been done using a neuro-visual model of figure ground segregation. The Local Binary Pattern (LBP) is taken as characteristic feature of a face with expression. This pattern gets evolved in the temporal domain over the sequence. The dynamics of the pattern, starting from a neutral face, is characterised by Hausdorff distance. Back Propagation (BP) Neural Networks are trained to estimate the expression intensity level of the basic expressions.

Keywords

backpropagation; emotion recognition; face recognition; image sequences; neural nets; Hausdorff distance; backpropagation neural network; binary face image sequence; facial expression intensity estimation; figure ground segregation; local binary pattern; neurovisual model; neutral face; temporal domain; Estimation; Face; Facial features; Humans; Information processing; Psychology; Video sequences; BP Neural Network; Expression intensity; Figure Ground Segregation; Hausdorff distance; Local Binary Pattern;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Information Processing (ICIIP), 2011 International Conference on

Conference_Location

Himachal Pradesh

Print_ISBN

978-1-61284-859-4

Type

conf

DOI

10.1109/ICIIP.2011.6108935

Filename

6108935