TY - JOUR
T1 - The contribution of different face parts to deep face recognition
AU - Lestriandoko, Nova Hadi
AU - Veldhuis, Raymond
AU - Spreeuwers, Luuk
N1 - Funding Information:
The research described in this article was supported by the Research and Innovation in Science and Technology Project (RISET-Pro) of the Ministry of Research, Technology, and Higher Education of the Republic of Indonesia (World Bank Loan No.8245-ID).
Publisher Copyright:
Copyright © 2022 Lestriandoko, Veldhuis and Spreeuwers.
Financial transaction number:
2500021279
PY - 2022/8/3
Y1 - 2022/8/3
N2 - 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.
AB - 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.
KW - average face
KW - deep face recognition
KW - face component contribution
KW - face exploitation
KW - face geometry
KW - face morphing
KW - face texture
UR - http://www.scopus.com/inward/record.url?scp=85136221140&partnerID=8YFLogxK
U2 - 10.3389/fcomp.2022.958629
DO - 10.3389/fcomp.2022.958629
M3 - Article
AN - SCOPUS:85136221140
SN - 2624-9898
VL - 4
SP - 1
EP - 16
JO - Frontiers in Computer Science
JF - Frontiers in Computer Science
M1 - 958629
ER -