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Journal Article
What is the most important facial part for face recognition?
- Authors
- Jong-won Moon, Ho-Sub Yoon
- Issue Date
- 2025-06
- Citation
- ETRI Journal, v.권호미정, pp.1-9
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원
- Language
- English
- Type
- Journal Article
- Abstract
- In typical scenarios in which parts of the face are occluded by objects such as masks, sunglasses, hats, or scarves, previous studies have focused on analyzing how the recognition rate varies depending on the degree and location of occlusion, and several approaches have been proposed for detecting occluded facial areas and recognizing partial faces. However, in this study, we aim to determine which facial regions are the most crucial for occluded face recognition. Identifying in advance which features of a partial face influence recognition performance the most could help prediction and enhance recognition accuracy. To evaluate performance based on the direction and position of the occluded areas, three common deep learning-based face recognition models (ArcFace, MobileFaceNet, and iResNet) are compared using the well-known public face datasets, LFW, CFP-FP, AgeDB, and IJB-C. Extensive experiments confirmed that the eye-centered horizontal and nose-centered vertical regions are the most critical for face recognition. When recognition was performed using only these two regions as input, the models achieved high recognition accuracy despite the absence of other facial features.
- KSP Keywords
- Learning-based, Occluded face recognition, Recognition Rate, Recognition model, Recognition performance, deep learning(DL), facial features, performance based, recognition accuracy
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
