Issue |
ITM Web Conf.
Volume 40, 2021
International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|
|
---|---|---|
Article Number | 03005 | |
Number of page(s) | 6 | |
Section | Computing | |
DOI | https://doi.org/10.1051/itmconf/20214003005 | |
Published online | 09 August 2021 |
Identification of Lost Children using Face Aging with Conditional GAN
1 Ramrao Adik Institute of Technology, Navi Mumbai, India
* e-mail: amishapupala20@gmail.com
** e-mail: samruddhimokal10@gmail.com
*** e-mail: panditneha124@gmail.com
**** e-mail: smita.bharne@rait.ac.in
Face recognition technology is a big area that consists of the many features in it but it also comes with some of the factors which affect this technology, one of the factors is Face aging which makes face recognition more difficult. As in India, a large number of children go missing every year. Also just using a photograph is not enough for the process to proceed smoothly and it results in a huge percentage of the missing child cases remain untraced. This paper presents a novel use of face recognition with face aging to overcome the limitation of existing systems. The proposed system has a portal where the public can upload an image of a suspected child and also have a feature where searching for any lost child is possible. The proposed system has mainly concentrated on an Age Conditional generative adversarial network (C-GAN) algorithm for face aging and the FaceNet algorithm for face feature extraction and face recognition.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.