Facial Expression Recognition using Convolutional Neural Network with Data Augmentation

被引：0
|
作者：
Ahmed, Tawsin Uddin [1 ]
Hossain, Sazzad [2 ]
Hossain, Mohammad Shahadat [1 ]
Ul Islam, Raihan [3 ]
Andersson, Karl [3 ]
机构：
[1] Univ Chittagong, Dept Comp Sci & Engn, Chittagong, Bangladesh
[2] Univ Liberal Arts Bangladesh, Dept Comp Sci & Engn, Dhaka, Bangladesh
[3] Lulea Univ Technol, Dept Comp Sci Elect & Space Engn, Skelleftea, Sweden
来源：
2019 JOINT 8TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV) AND 2019 3RD INTERNATIONAL CONFERENCE ON IMAGING, VISION & PATTERN RECOGNITION (ICIVPR) WITH INTERNATIONAL CONFERENCE ON ACTIVITY AND BEHAVIOR COMPUTING (ABC) | 2019年
基金：
瑞典研究理事会;
关键词：
Convolutional neural network; data augmentation; validation accuracy; emotion detection; EXPERT-SYSTEM;
D O I：
10.1109/iciev.2019.8858529
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Detecting emotion from facial expression has become an urgent need because of its immense applications in artificial intelligence such as human-computer collaboration, data-driven animation, human-robot communication etc. Since it is a demanding and interesting problem in computer vision, several works had been conducted regarding this topic. The objective of this research is to develop a facial expression recognition system based on convolutional neural network with data augmentation. This approach enables to classify seven basic emotions consist of angry, disgust, fear, happy, neutral, sad and surprise from image data. Convolutional neural network with data augmentation leads to higher validation accuracy than the other existing models (which is 96.24%) as well as helps to overcome their limitations.
引用
收藏
页码：336 / 341
页数：6
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