Effective Face Detection Feature Extraction & Neural Network Based Approaches for Facial Expression Recognition

被引：0
|
作者：
Muttu, Yeshudas [1 ]
Virani, H. G. [1 ]
机构：
[1] Goa Coll Engn, Elect & Telecommun Dept, Veling, Goa, India
来源：
2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING (ICIP) | 2015年
关键词：
BPN; Concatenated Histogram; LBP; RBF; Region of Interest;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Face expression recognition is a typical task to make human and machine interaction possible. Besides this, medical science and other applications demand for such system. This paper focusses on importance of face detection and its feature parts. For this, Viola Jones algorithm was implemented. The crucial part of this paper is feature extraction and the algorithm used for the purpose is modified local binary patterns algorithm. The results of feature extraction algorithms are compared to that in the literature to show the limitations of the existing algorithms and their suitabilility for this application. Neural network based approaches are used for classification of facial expressions. This paper enumerates two classification techniques for the facial expressions. The system performs well by the method used by us and gives efficient results. This was experimented using the Taiwanian database and the Japanese database.
引用
收藏
页码：102 / 107
页数：6
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