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Face Recognition Methods & Applications

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arxiv 1403.0485 v1 pith:NKZAALP7 submitted 2014-03-03 cs.CV

classification cs.CV
keywords facerecognitionimagesecuritysystemdescribesmethodssection
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition

    cs.SD 2025-02 conditional novelty 5.0 of 10

    A gradient-norm-regularized fine-tuning method, GN-FT, removes backdoor behaviors from audio speech recognition models while keeping clean accuracy high.

  2. Pura: An Efficient Privacy-Preserving Solution for Face Recognition

    cs.CV 2025-05 conditional novelty 4.0 of 10

    Pura lets twin cloud servers perform face recognition directly on encrypted feature vectors using threshold Paillier encryption, with exact accuracy and up to 16x speedup at database size 1,000.

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