The contribution of different face parts to deep face recognition

Author:

Lestriandoko Nova Hadi,Veldhuis Raymond,Spreeuwers Luuk

Abstract

The development of face recognition improvements still lacks knowledge on what parts of the face are important. In this article, the authors present face parts analysis to obtain important recognition information in a certain area of the face, more than just the eye or eyebrow, from the black box perspective. In addition, the authors propose a more advanced way to select parts without introducing artifacts using the average face and morphing. Furthermore, multiple face recognition systems are used to analyze the face component contribution. Finally, the results show that the four deep face recognition systems produce a different behavior for each experiment. However, the eyebrows are still the most important part of deep face recognition systems. In addition, the face texture played an important role deeper than the face shape.

Publisher

Frontiers Media SA

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Computer Science (miscellaneous)

Reference34 articles.

1. Face recognition with local binary patterns;Ahonen,2004

2. Robust facial expression recognition using local binary patterns;Caifeng;IEEE Int. Conf. Image Process.,2005

3. Histograms of oriented gradients for human detection;Dalal,2005

4. The effect of wearing a mask on face recognition performance: an exploratory study;Damer,2020

5. ArcFace: additive angular margin loss for deep face recognition;Deng,2019

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. E2F-Net: Eyes-to-face inpainting via StyleGAN latent space;Pattern Recognition;2024-08

2. The Role of Facial Hair on Roman Emperors' Face Recognition;2024 12th International Workshop on Biometrics and Forensics (IWBF);2024-04-11

3. The Impact of Eyebrows Region on Deep Face Recognition;2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA);2023-10-04

4. Synthetic Face Generation Through Eyes-to-Face Inpainting;2023 IEEE International Joint Conference on Biometrics (IJCB);2023-09-25

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3