广东工业大学学报2024，Vol.41Issue(3)：62-70,109,10.DOI:10.12052/gdutxb.230052
基于红外可见光融合的复杂环境下人脸识别方法
Face Recognition Method in Complex Environment Based on Infrared Visible Fusion
摘要
Abstract
With the development of deep learning methods,the accuracy and speed of face recognition based on visible light in ideal environments have reached an excellent level.However,in complex environments such as low light,the lack of a light source keeps visible images from reflecting face details,resulting in reduced or even invalid face recognition.Aiming at the problems in this issue,a face recognition method in complex environments based on infrared-visible light fusion is proposed.Firstly,an infrared and visible fusion recognition network combining CNN and Transformer is introduced,specifically designed for low illumination environments.This network combines CNN and visual Transformer in parallel to form a single-mode feature fusion module,which is utilized to effectively utilize local details and global context information from the source image.Additionally,a multimodal feature fusion strategy based on the average difference of modes is proposed to enhance the distinctive expression of different regional features in the source image.Secondly,a lightweight face recognition network MobileFaceNet-Coo and an adaptive recognition strategy based on edge-cloud collaboration are proposed in order to solve the problem of large and slow fusion recognition network models in practical applications.This strategy selects the recognition model through image quality and effectively utilizes hardware resources.Experimental results demonstrate that the recognition rate of fused infrared light is 13.96 percentage point higher than that of visible light alone.Real-world project result shows that this method significantly improves real-time and accuracy of face recognition in complex environments.关键词
人脸识别/图像融合/低照度/TransformerKey words
face recognition/image fusion/low illumination/Transformer分类
信息技术与安全科学引用本文复制引用
冯广,鲍龙..基于红外可见光融合的复杂环境下人脸识别方法[J].广东工业大学学报,2024,41(3):62-70,109,10.基金项目
国家自然科学基金资助项目(62237001) （62237001）
广东省哲学社会科学项目(GD23YJY08) （GD23YJY08）
