A Lifelong Learning Approach for Improving Accurate Face Recognition
- 10.2991/icaita-16.2016.2How to use a DOI?
- face recognition; meachine learning; neural network; lifelong learning; artificial intelligence
With the popularity of artificial intelligence and computer vision, an increasing number of software engineers attempt to make their systems be able to recognize the user, through the way of face recognition, e.g., Characteristic Points (i.e., CP)-based face recognition. Generally, the traditional CP-based face recognition only work when the user’s face is not much different from the one that stores in the system. However, users’ faces can change a lot intentionally or unintentionally, which brings a great challenge for correct face recognition. In view of this challenge, a novel face recognition approach LL-FR (Lifelong Learning-based Face Recognition) is put forward in this paper. Concretely, the system stores not only the face image that the user registered, but also the images every time when it recognizes the user’s face. Afterwards, the system makes the future recognition of the user based on all the previous faces of him/her. Finally, through a set of experiments, we demonstrate the feasibility of our approach.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhangqu Yu PY - 2016/01 DA - 2016/01 TI - A Lifelong Learning Approach for Improving Accurate Face Recognition BT - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications PB - Atlantis Press SP - 6 EP - 8 SN - 1951-6851 UR - https://doi.org/10.2991/icaita-16.2016.2 DO - 10.2991/icaita-16.2016.2 ID - Yu2016/01 ER -