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
收藏
页码：445 / 449
页数：5
相关论文
共 50 条
  • [41] Facial Expression Recognition Using 3D Convolutional Neural Network
    Byeon, Young-Hyen
    Kwak, Keun-Chang
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2014, 5 (12) : 107 - 112
  • [42] Facial Expression Recognition using Discrete Cosine Transform & Artificial Neural Network
    Khan, Abdul Saboor
    Shafi, Imran
    Anas, Muhammad
    Yousuf, Bilal M.
    Abbas, Muhammad Jamshed
    Noor, Aqib
    2019 22ND IEEE INTERNATIONAL MULTI TOPIC CONFERENCE (INMIC), 2019, : 83 - 87
  • [43] Facial expression recognition using discrete cosine transform artificial neural network
    Saboor Khan, Abdul
    Shafi, Imran
    Anas, Muhammad
    Yousuf, Bilal M
    Abbas, Muhammad Jamshed
    Noor, Aqib
    Proceedings - 22nd International Multitopic Conference, INMIC 2019, 2019,
  • [44] Facial Expression Recognition Using a Multi-level Convolutional Neural Network
    Hai-Duong Nguyen
    Yeom, Soonja
    Oh, Il-Seok
    Kim, Kyoung-Min
    Kim, Soo-Hyung
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (ICPRAI 2018), 2018, : 217 - 221
  • [45] A neural network facial expression recognition system using unsupervised local processing
    Franco, L
    Treves, A
    ISPA 2001: PROCEEDINGS OF THE 2ND INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS, 2001, : 628 - 632
  • [46] Facial expression recognition using convolutional neural network with weighted loss function
    Luan, Jiawei
    2020 IEEE 3RD INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SIGNAL PROCESSING (ICICSP 2020), 2020, : 252 - 257
  • [47] Facial Expression Recognition with PCA and LBP Features Extracting from Active Facial Patches
    Liu, Yanpeng
    Cao, Yuwen
    Li, Yibin
    Liu, Ming
    Song, Rui
    Wang, Yafang
    Xu, Zhigang
    Ma, Xin
    2016 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE RCAR), 2016, : 368 - 373
  • [48] Facial Expression Recognition Using Enhanced Convolution Neural Network with Attention Mechanism
    Prabhu, K.
    SathishKumar, S.
    Sivachitra, M.
    Dineshkumar, S.
    Sathiyabama, P.
    COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2022, 41 (01): : 415 - 426
  • [49] Expression recognition using LGDPHS based facial key parts
    Higashi, Atsushi
    Fukumizu, Yohei
    Izumi, Tomonori
    Yamauchi, Hironori
    Journal of the Institute of Image Electronics Engineers of Japan, 2012, 41 (05) : 496 - 505
  • [50] FACIAL FRECKLES RECOGNITION USING CONVOLUTIONAL NEURAL NETWORK
    Hu, Liang
    Chen, Li
    Tian, Jing
    2017 INTERNATIONAL SYMPOSIUM ON INTELLIGENT SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ISPACS 2017), 2017, : 145 - 148
12345