集成技术2024，Vol.13Issue(1)：72-81,10.DOI:10.12146/j.issn.2095-3135.20230606001
基于多光谱和面部多区域联合的人脸活体检测算法
Face Anti-Spoofing Algorithm Based on Combination of Multiple Facial Regions Using Multi-Spectral Images
邓可望 1赵娟 2肖振中 3师少光 3朱亮4
作者信息
- 1. 中国科学院深圳先进技术研究院 深圳 518055||奥比中光科技集团股份有限公司 深圳 518062
- 2. 中国科学院深圳先进技术研究院 深圳 518055
- 3. 奥比中光科技集团股份有限公司 深圳 518062
- 4. 深圳奥芯微视科技有限公司 深圳 518062
- 折叠
摘要
Abstract
In the research of face anti-spoofing(FAS),most related techniques are dependent to the RGB images or IR images,which lack sufficient biometric features and are vulnerable to ever-advancing presentation attacks.In this paper,a Transformer model based on combination of multiple facial regions is proposed to introduce multi-spectral technology into the task of facial live detection,aiming to obtain unique biological features of the real faces and increase the distinguishability from the fake faces.In the proposed model,multi-spectral images are utilized to broaden the spectral dimension for more reflection information,which can identify various materials.Besides,a spectral normalization method is preprocessed pixel by pixel to reduce the impacts of the environmental illumination variations and enhance the consistency of facial reflection features regionally.Then multiple core facial regions,like eyes,nose,mouth and cheeks,are selected as input of the deep learning model.Furthermore,a Transformer-based model is constructed to obtain both local regional features and inter association features of different facial regions,which are integrated into complete facial biometric features to achieve facial live detection.On the author's self-built multi-spectral facial datasets,the results show that the proposed method achieved an accuracy of 95.72%for and a misclassification of 5.10%for live detection,which is superior to commonly used FAS models.关键词
活体检测/多光谱/Transformer 模型/深度学习Key words
anti-spoofing/multi-spectral/Transformer model/deep learning分类
信息技术与安全科学引用本文复制引用
邓可望,赵娟,肖振中,师少光,朱亮..基于多光谱和面部多区域联合的人脸活体检测算法[J].集成技术,2024,13(1):72-81,10.
