Facial Expression Recognition Using Lbp Template of Facial Parts and Multilayer Neural Network

被引：0

作者：

Kauser, Nazima ^{[1
]}

Sharma, Jitendra ^{[1
]}

机构：

[1] Shree Vaishnav Inst Technol & Sci, Indore, Madhya Pradesh, India

来源：

2017 INTERNATIONAL CONFERENCE ON I-SMAC (IOT IN SOCIAL, MOBILE, ANALYTICS AND CLOUD) (I-SMAC) | 2017年

关键词：

Local Binary Pattern; Multilayer Feed forward Neural Network; Automatic Face Detection; Fletcher-Reeves Conjugate gradient method;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Various methods do exist for facial expression recognition and it's still a challenging task to get accurate results on unseen images due to lack of generalizability. To improve generalization Local Binary Pattern (LBP) are used as feature extraction. Facial parts like eyes, nose and mouth are detected and template is created for each image in dataset. The template of reference image is matched with training image and classified with Neural Network. We train and test with images from the Kohn-Kanade Database. We obtain recognition rate of 95.83% for person independent analysis. Proposed method shows a significant improvement in the recognition rate as compare to existing methods.

引用

页码：445 / 449

页数：5

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