A review on state-of-the-art face recognition approaches

Zahid Mahmood, Nazeer Muhammad*, Nargis Bibi, Tauseef Ali

*Corresponding author for this work

    Research output: Contribution to journalReview articleAcademicpeer-review

    43 Citations (Scopus)

    Abstract

    Automatic Face Recognition (FR) presents a challenging task in the field of pattern recognition and despite the huge research in the past several decades; it still remains an open research problem. This is primarily due to the variability in the facial images, such as non-uniform illuminations, low resolution, occlusion, and/or variation in poses. Due to its non-intrusive nature, the FR is an attractive biometric modality and has gained a lot of attention in the biometric research community. Driven by the enormous number of potential application domains, many algorithms have been proposed for the FR. This paper presents an overview of the state-of-the-art FR algorithms, focusing their performances on publicly available databases. We highlight the conditions of the image databases with regard to the recognition rate of each approach. This is useful as a quick research overview and for practitioners as well to choose an algorithm for their specified FR application. To provide a comprehensive survey, the paper divides the FR algorithms into three categories: (1) intensity-based, (2) video-based, and (3) 3D based FR algorithms. In each category, the most commonly used algorithms and their performance is reported on standard face databases and a brief critical discussion is carried out.

    Original languageEnglish
    Article number1750025
    JournalFractals
    Volume25
    Issue number2
    DOIs
    Publication statusPublished - 1 Apr 2017

    Keywords

    • Biometrics
    • Face detection
    • Face recognition
    • Recognition rate

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