Multi-branch Face Quality Assessment for Face Recognition

doi:10.1109/ICCT46805.2019.8947255

	Multi-branch Face Quality Assessment for Face Recognition
	Lijun, Zhang 1,2; Xiaohu, Shao 1,2; Fei, Yang 1,2; Pingling, Deng 1,2; Xiangdong, Zhou 1,2; Yu, Shi 1,2
	2019
会议日期	October 16, 2019 - October 19, 2019
会议地点	Xi'an, China
DOI	10.1109/ICCT46805.2019.8947255
页码	1659-1664
英文摘要	The quality of face images varies due to complex environmental factors, and face images with extremely poor qualities would deteriorate the performance of face recognition. As one of the pre-processing modules of face recognition, face quality assessment needs to consider both environment factors and practical applications. In this paper, we propose a multibranch face quality assessment (MFQA) algorithm considering comprehensive factors acting as a reliable reference for its following recognition. A light-weight convolution neural network (CNN) is used for face image feature extraction, and quality scores corresponding with alignment, visibility, deflection and clarity are predicted by multi-branch layers. Moreover, a score fusion module is implemented by fusing the above scores to obtain a final quality confidence. Compared with other relevant quality assessment works, our method is quite suitable for practical applications because of its better performance, faster speed and smaller model size. Experiments show that our proposed method is able to assess face quality objectively, and the performance of face recognition is significantly improved by introducing our approach into its training and testing procedures. © 2019 IEEE.
会议录	19th IEEE International Conference on Communication Technology, ICCT 2019
语种	英语
内容类型	会议论文
源URL	[http://119.78.100.138/handle/2HOD01W0/9790]
专题	中国科学院重庆绿色智能技术研究院
作者单位	1.Chongqing Institute of Green and Intelligent Technology, CAS, China; 2.University of Chinese Academy of Sciences, Chinese Academy of Sciences, Chongqing, China
推荐引用方式 GB/T 7714	Lijun, Zhang,Xiaohu, Shao,Fei, Yang,et al. Multi-branch Face Quality Assessment for Face Recognition[C]. 见:. Xi'an, China. October 16, 2019 - October 19, 2019.