Summary of Unmasking the Uniqueness: a Glimpse Into Age-invariant Face Recognition Of Indigenous African Faces, by Fakunle Ajewole et al.
Unmasking the Uniqueness: A Glimpse into Age-Invariant Face Recognition of Indigenous African Faces
by Fakunle Ajewole, Joseph Damilola Akinyemi, Khadijat Tope Ladoja, Olufade Falade Williams Onifade
First submitted to arxiv on: 13 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper addresses the underrepresentation of African ethnicity in Age-Invariant Face Recognition (AIFR) research, leveraging a dataset of 5,000 indigenous African faces (FAGE_v2). A pre-trained deep learning model (VGGFace) is fine-tuned on FAGE_v2 to achieve an accuracy of 81.80%. The authors also explore the performance on an African-American subset of the CACD dataset, obtaining a best accuracy of 91.5%. The study highlights significant differences in recognition accuracies between indigenous and non-indigenous Africans. The proposed AIFR system aims to mitigate biases in facial image analysis research by focusing on underrepresented populations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to recognize people based only on their faces, without knowing how old they are. This is called Age-Invariant Face Recognition (AIFR). In the past, many AIFR studies have focused on white people and ignored black people from Africa. To fix this problem, researchers created a special dataset with 5,000 photos of African faces. They used a computer model to try to recognize these faces and got an accuracy rate of 81.80%. The authors also tested their method on some American-African faces and did even better, with an accuracy rate of 91.5%. This shows that there is a big difference in how well AI can recognize black people from Africa versus other groups. |
Keywords
» Artificial intelligence » Deep learning » Face recognition
