Does Face Recognition Error Echo Gender Classification Error?
| Autor: | Kevin W. Bowyer, Michael C. King, Ying Qiu, Vitor Albiero |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Artificial Intelligence business.industry Computer science Computer Vision and Pattern Recognition (cs.CV) Echo (computing) Computer Science - Computer Vision and Pattern Recognition Pattern recognition Open source software Facial recognition system Image (mathematics) Computer Science - Computers and Society Statistical classification Artificial Intelligence (cs.AI) Face (geometry) Computers and Society (cs.CY) Match rate Image pair Artificial intelligence business |
| Zdroj: | IJCB |
| Popis: | This paper is the first to explore the question of whether images that are classified incorrectly by a face analytics algorithm (e.g., gender classification) are any more or less likely to participate in an image pair that results in a face recognition error. We analyze results from three different gender classification algorithms (one open-source and two commercial), and two face recognition algorithms (one open-source and one commercial), on image sets representing four demographic groups (African-American female and male, Caucasian female and male). For impostor image pairs, our results show that pairs in which one image has a gender classification error have a better impostor distribution than pairs in which both images have correct gender classification, and so are less likely to generate a false match error. For genuine image pairs, our results show that individuals whose images have a mix of correct and incorrect gender classification have a worse genuine distribution (increased false non-match rate) compared to individuals whose images all have correct gender classification. Thus, compared to images that generate correct gender classification, images that generate gender classification errors do generate a different pattern of recognition errors, both better (false match) and worse (false non-match). |
| Databáze: | OpenAIRE |
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