A Benchmark of Facial Recognition Pipelines and Co-Usability Performances of Modules

Authors : Sefik Serengil, Alper Özpınar

Pages : 95-107

Doi:10.17671/gazibtd.1399077

View : 340 | Download : 366

Publication Date : 2024-04-30

Article Type : Research Paper

Abstract :Researchers from leading technology companies, prestigious universities worldwide, and the open-source community have made substantial strides in the field of facial recognition studies in recent years. Experiments indicate that facial recognition approaches have not only achieved but surpassed human-level accuracy. A contemporary facial recognition process comprises four key stages: detection, alignment, representation, and verification. Presently, the focus of facial recognition research predominantly centers on the representation stage within the pipelines. This study conducted experiments exploring alternative combinations of nine state-of-the-art facial recognition models, six cutting-edge face detectors, three distance metrics, and two alignment modes. The co-usability performances of implementing and adapting these modules were assessed to precisely gauge the impact of each module on the pipeline. Theoretical and practical findings from the study aim to provide optimal configuration sets for facial recognition pipelines.
Keywords : yüz tanıma, yüz tanıma, yüz doğrulama, deepface, vektör modeller