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DOI: 10.14569/IJACSA.2019.0101262
PDF

Joint Demographic Features Extraction for Gender, Age and Race Classification based on CNN

Author 1: Zaheer Abbas
Author 2: Sajid Ali
Author 3: Muhammad Ashad Baloch
Author 4: Hamida Ilyas
Author 5: Moneeb Ahmad
Author 6: Mubasher H. Malik
Author 7: Noreen Javaid
Author 8: Tanvir Fatima Naik Bukht

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 12, 2019.

  • Abstract and Keywords
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Abstract: Automatic verification and identification of face from facial image to obtain good accuracy with huge dataset of training and testing to using face attributes from images is still challengeable. Hence proposing efficient and accurate facial image identification and classification based of facial attributes is important task. The prediction from human face image is much complex. The proposed research work for automatic gender, age and race classification is based on facial features and Convolutional Neural Network (CNN). The proposed study uses the physical appearance of human face to predict age, gender and race. The proposed methodology consists of three sub systems, Gender, Ageing and Race. Therefore different feature are extracted for every sub system. These features are extracted by using Primary, Secondary features, Face Angle, Wrinkle Analysis, LBP and WLD. The accuracy of classification is based on these features. CNN used to classify by using these features. The proposed study has been evaluated and tested on large database MORPH II and UTKF. The performance of proposed system is compared with state of art techniques.

Keywords: Appearance features; age; gender; wrinkle analysis; face angle; classification; race; LBP

Zaheer Abbas, Sajid Ali, Muhammad Ashad Baloch, Hamida Ilyas, Moneeb Ahmad, Mubasher H. Malik, Noreen Javaid and Tanvir Fatima Naik Bukht, “Joint Demographic Features Extraction for Gender, Age and Race Classification based on CNN” International Journal of Advanced Computer Science and Applications(IJACSA), 10(12), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101262

@article{Abbas2019,
title = {Joint Demographic Features Extraction for Gender, Age and Race Classification based on CNN},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101262},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101262},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {12},
author = {Zaheer Abbas and Sajid Ali and Muhammad Ashad Baloch and Hamida Ilyas and Moneeb Ahmad and Mubasher H. Malik and Noreen Javaid and Tanvir Fatima Naik Bukht}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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