# Face Recognition Methods & Applications

arXiv: https://arxiv.org/abs/1403.0485 · HTML: https://mlsanity.com/paper/1403.0485/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Mar 2014.

## Built on by (most cited first, 11 of 11)

- [Dodging Attack Using Carefully Crafted Natural Makeup](https://mlsanity.com/paper/2109.06467/) (2021)
- [VisCUIT: Visual Auditor for Bias in CNN Image Classifier](https://mlsanity.com/paper/2204.05899/) (2022)
- [Unveiling and Mitigating Backdoor Vulnerabilities based on Unlearning Weight Changes and Backdoor Activeness](https://mlsanity.com/paper/2405.20291/) (2024)
- [New Benchmarks for Asian Facial Recognition Tasks: Face Classification with Large Foundation Models](https://mlsanity.com/paper/2310.09756/) (2023)
- [DivTrackee versus DynTracker: Promoting Diversity in Anti-Facial Recognition against Dynamic FR Strategy](https://mlsanity.com/paper/2501.06533/) (2025)
- [An Improved Real-Time Face Recognition System at Low Resolution Based on Local Binary Pattern Histogram Algorithm and CLAHE](https://mlsanity.com/paper/2104.07234/) (2021)
- [Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition](https://mlsanity.com/paper/2502.01152/) (2025)
- [Fusing Pruned and Backdoored Models: Optimal Transport-based Data-free Backdoor Mitigation](https://mlsanity.com/paper/2408.15861/) (2024)
- [AdvSecureNet: A Python Toolkit for Adversarial Machine Learning](https://mlsanity.com/paper/2409.02629/) (2024)
- [Unified Face Matching and Physical-Digital Spoofing Attack Detection](https://mlsanity.com/paper/2501.09635/) (2025)
- [Pura: An Efficient Privacy-Preserving Solution for Face Recognition](https://mlsanity.com/paper/2505.15476/) (2025)

## Abstract (arXiv)

Face recognition presents a challenging problem in the field of image analysis and computer vision. The security of information is becoming very significant and difficult. Security cameras are presently common in airports, Offices, University, ATM, Bank and in any locations with a security system. Face recognition is a biometric system used to identify or verify a person from a digital image. Face Recognition system is used in security. Face recognition system should be able to automatically detect a face in an image. This involves extracts its features and then recognize it, regardless of lighting, expression, illumination, ageing, transformations (translate, rotate and scale image) and pose, which is a difficult task. This paper contains three sections. The first section describes the common methods like holistic matching method, feature extraction method and hybrid methods. The second section describes applications with examples and finally third section describes the future research directions of face recognition.