A Machine Learning Algorithm of Human-Computer-Interface Application-An AdaRank Model Approach to Facial Expression Recognition

DOI

10.2991/iccsee.2013.42How to use a DOI?

Keywords

facial expression recognition, landmarks, facial feature, AdaRank

Abstract

A completely automatic facial expression recognition system is presented in this paper, which consists of three main procedures. The first is based on skin color blocks and geometrical properties applied to eliminate the skin color regions that do not belong to the face in the HSV color space. Than we find proper ranges of eyes, mouth, and eyebrows according to the positions of pupils and center of a mouth. Subsequently, we perform both the edge detection and binarization operations on the above ranged images to obtain 16 landmarks. After manipulating these landmarks, 16 characteristic distances are the facial feature produced to represent a kind of expressions. Finally, we subtract the 16 characteristic distances of a neutral face from the 16 characteristic distances of a certain expression to acquire its 16 displacement values fed to a classifier with an incremental learning scheme, which can identify six kinds of expressions: joy, anger, surprise, fear, sadness, and neutral. We choose the AdaRank model as the core technique to implement our strong facial expression classifier. Our model, referred to as AdaRank, repeatedly constructs classifiers on the basis of re-weighted training data and finally linearly combines the classifiers for making ranking predictions. Through conducting many experiments, the statistics of performance reveals that the accuracy rate of our facial expression recognition system reaches more than 95%.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Chang-Yi Kao
AU  - Chin-Shyurng Fahn
PY  - 2013/03
DA  - 2013/03
TI  - A Machine Learning Algorithm of Human-Computer-Interface Application-An AdaRank Model Approach to Facial Expression Recognition
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 160
EP  - 163
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.42
DO  - 10.2991/iccsee.2013.42
ID  - Kao2013/03
ER  -