Yüz Tanıma Üretim Hatlarının ve Modüllerinin Birlikte Kullanımının Karşılaştırılması

Year 2024, , 95 - 107, 30.04.2024

Sefik Serengil , Alper Özpınar

https://doi.org/10.17671/gazibtd.1399077

Cited By: 1

Abstract

BSon yıllarda, büyük teknoloji şirketleri, dünyanın önde gelen üniversiteleri ve açık kaynak topluluğundan gelen araştırmacılar, yüz tanıma alanında önemli ilerlemeler kaydetmişlerdir. Yapılan deneyler, yüz tanıma yaklaşımlarının insan düzeyinde doğruluk sağladığını ve hatta aştığını göstermektedir. Modern bir yüz tanıma süreci genellikle dört aşamadan oluşur: algılama, hizalama, temsil ve doğrulama. Mevcut yüz tanıma çalışmaları genellikle üretim hatlarındaki temsil aşamasına odaklanmıştır. Bu çalışmada, dokuz farklı son teknoloji yüz tanıma modeli, altı son teknoloji yüz dedektörü, üç mesafe ölçümü ve iki hizalama modunun farklı kombinasyonları için çeşitli deneyler gerçekleştirilmiştir. Bu modüllerin uygulanması ve uyumlu hale getirilmesinin genel performansları, her bir modülün üretim hattındaki spesifik etkisini belirlemek amacıyla değerlendirilmiştir. Çalışmanın teorik ve pratik sonucu olarak, yüz tanıma hatları için en iyi konfigürasyon setlerinin paylaşılması hedeflenmektedir.

Keywords

yüz tanıma, yüz tanıma, yüz doğrulama, deepface, vektör modeller

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

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

facial recognition, face verification, deepface, vector models

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