Data-Specific Adaptive Threshold for Face Recognition and Authentication
Journal
Proceedings - 2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019
Pages
153-156
Date Issued
2019
Author(s)
Abstract
Many face recognition systems boost the performance using deep learning models, but only a few researches go into the mechanisms for dealing with online registration. Although we can obtain discriminative facial features through the state-of-the-art deep model training, how to decide the best threshold for practical use remains a challenge. We develop a technique of adaptive threshold mechanism to improve the recognition accuracy. We also design a face recognition system along with the registering procedure to handle online registration. Furthermore, we introduce a new evaluation protocol to better evaluate the performance of an algorithm for real-world scenarios. Under our proposed protocol, our method can achieve a 22% accuracy improvement on the LFW dataset. ? 2019 IEEE.
Subjects
Authentication; Deep learning; Online systems; Accuracy Improvement; Adaptive thresholds; Evaluation protocol; Face authentication; Face recognition and authentications; Face recognition systems; Real-world scenario; Recognition accuracy; Face recognition
SDGs
Type
conference paper