Performance analysis of canny edge detection for illumination invariant Facial Expression recognition

Face perception is a very important component of human cognition. We can judge the person's mood and mental status through his/her expressions. In other words, the most expressive way human display emotion is through facial expressions. And hence facial expression recognition has become an acti...

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Main Authors: Shah, Zankhana H., Kaushik, Vikram
Format: Conference Proceeding
Language:English
Subjects:
Euclidian Distance
Eyebrows
Face recognition
Facial Expression Recognition
Geometry
Glass
Illumination Invariance
Image recognition
Indian Facial Expression
Mouth
Neural Network
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Kaushik, Vikram
description Face perception is a very important component of human cognition. We can judge the person's mood and mental status through his/her expressions. In other words, the most expressive way human display emotion is through facial expressions. And hence facial expression recognition has become an active research area in the field of human computer interaction. The work in this paper concentrates on images having different illuminations and analyzes the performance of canny edge detection method with two classifiers, Euclidian distance and neural network. The results are tested on JAFFE (Japanese Female Facial Expression) database, available in public domain and IFE (Indian Facial Expression) database which is self created.
doi_str_mv 10.1109/IIC.2015.7150809
format conference_proceeding
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Euclidian Distance
Eyebrows
Face recognition
Facial Expression Recognition
Geometry
Glass
Illumination Invariance
Image recognition
Indian Facial Expression
Mouth
Neural Network
title Performance analysis of canny edge detection for illumination invariant Facial Expression recognition
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