Affiliation:
1. School of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China
2. School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China
Abstract
Face recognition technology is a powerful means to capture biological facial features and match facial data in existing databases. With the advantages of noncontact and long-distance implementation, it is being used in more and more scenarios. Affected by factors such as light, posture, and background environment, the face images captured by the device are still insufficient in the recognition rate of existing face recognition models. We propose an AB-FR model, a convolutional neural network face recognition method based on BiLSTM and attention mechanism. By adding an attention mechanism to the CNN model structure, the information from different channels is integrated to enhance the robustness of the network, thereby enhancing the extraction of facial features. Then, the BiLSTM method is used to extract the timing characteristics of different angles or different time photos of the same person so that convolutional blocks can obtain more face detail information. Finally, we used the cross-entropy loss function to optimize the model and realize the correct face recognition. The experimental results show that the improved network model indicates better identification performance and stronger robustness on some public datasets (such as CASIA-FaceV5, LFW, MTFL, CNBC, and ORL). Besides, the accuracy rate is 99.35%, 96.46%, 97.04%, 97.19%, and 96.79%, respectively.
Funder
Basic Research Program (Free Exploration) of Shanxi Province
Subject
General Mathematics,General Medicine,General Neuroscience,General Computer Science
Reference35 articles.
1. A Review of Face Recognition Technology
2. Face detection algorithm based on geometric features and new haar features;M. Yuangen;Sensors and Microsystems,2017
3. Face recognition method based on eigenface-grayscale transformation fusion;Z. Wang;Small Microcomputer System,2019
4. A face recognition method based on hidden Markov model;Z. Wang;Computer Applications and Software,2013
5. A Study on the Application and the Advancement of Deep Neural Network Algorithm
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