Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 68Biometric Identification and SecurityFace recognition and analysisFace and Expression Recognition

The DOI matches its Crossref record.

An Overview of Face Liveness Detection

Open access
Chakraborty, Saptarshi, Das, Dhrubajyoti·2014·International Journal on Information Theory

Abstract

Face recognition is a widely used biometric approach.Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods.But face recognition systems are vulnerable to spoof attacks made by non-real faces.It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs.A secure system needs Liveness detection in order to guard against such spoofing.In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection.This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions.A review of the latest works regarding face liveness detection works is presented.The main aim is to provide a simple path for the future development of novel and more secured face liveness detection approach.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.5121/ijit.2014.3202

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 18

  1. G. Kim, S.Eum, J. K. Suhr, D. I. Kim, K. R. Park, and J, Kim, Face liveness detection based on texture and frequency analyses, 5th IAPR International Conference on Biometrics (ICB), New Delhi, India. pp. 67-72, March 2012.
  2. J. Maatta, A. Hadid, M. Pietikainen, Face Spoofing Detection From Single images Using Micro- Texture Analysis, Proc. International Joint Conference on Biometrics (UCB 2011), Washington, D.C., USA.
  3. sooyeon Kim, Sunjin Yu, Kwangtaek Kim, Yuseok Ban, Sangyoun Lee, Face liveness detection using variable focusing, Biometrics (ICB), 2013 International Conference on, On page(s): 1 -6, 2013.
  4. H. K. Jee, S. U. Jung, and J. H. Yoo, Liveness detection for embedded face recognition system, International Journal of Biological and Medical Sciences, vol. 1(4), pp. 235-238, 2006.
  5. Wei Bao, Hong Li, Nan Li, and Wei Jiang, A liveness detection method for face recognition based on optical flow field, In Image Analysis and Signal Processing, 2009, IASP 2009, International Conference on, pages 233 -236, April 2009.
  6. K. Kollreider H. Fronthaler, and J. Bigun, Evaluating liveness by face images and the structure tensor, in Proc of 4th IEEE Workshop on Automatic Identification Advanced Technologies, Washington DC, USA, pp. 75-80, October 2005.
  7. Lin Sun, Gang Pan, Zhaohui Wu, Shihong Lao, Blinking-Based Live Face Detection Using Conditional Random Fields, ICB 2007, Seoul, Korea, International Conference, on pages 252-260, August 27-29, 2007.
  8. Jianwei Yang, Zhen Lei, Shengcai Liao, Li, S.Z, Face Liveness Detection with Component Dependent Descriptor, Biometrics (ICB), 2013 International Conference on Page(s): 1 -6, 2013.
  9. Andrea Lagorio, Massimo Tistarelli, Marinella Cadoni, Liveness Detection based on 3D Face Shape Analysis, Biometrics and Forensics (IWBF), 2013 International Workshop on Page(s): 1-4, 2013.
  10. X. Tan, Y. Li, J. Liu, and L. Jiang, Face liveness detection from a single image with sparse low rank bilinear discriminative model, in ECCV, 2010.
  11. B. Peixoto, C. Michelassi and A. Rocha, Face liveness detection under bad illumination conditions, In ICIP, pages 3557-3560, 2011.
  12. J. Li Y. Wang, T. Tan, and A.K. Jain, Live face detection based on the analysis of Fourier spectra, in Proc of Biometric Technology for Human Identification, Orlando, FL, USA. (SPIE 5404), pp. 296- 303, April 2004.
  13. Anil K. Jain, Patrick Flynn, Arun A. Ross, "Handbook of Biometrics", Springer, 2008.
  14. K. Kollreider, H. Fronthaler, M. I. Faraj, and J. Bigun, Real-time face detection and motion analysis with application in "liveness" assessment, IEEE Transactions on Information Forensics and Security, 2(3-2):548-558, 2007.
  15. K. Kollreider, H. Fronthaler, and J. Bigun, Non-intrusive liveness detection by face images, Image and Vision Computing, vol. 27(3), pp. 233-244, 2009.
  16. Jukka Komulainen, Abdenour Hadid, Matti Pietikainen, Context based Face Anti-Spoofing, Biometrics: Theory, Applications and Systems (BTAS), 2013 IEEE Sixth International Conference on Pages: 1-8, 2013.
  17. K. Kollreider, H. Fronthaler, and J. Bigun, Verifying Liveness by Multiple Experts in Face Biometrics, In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pages 1-6, 2008.
  18. T. Wang, J. Yang, Z. Lei, S. Liao, and S. Z. Li, Face Liveness Detection Using 3D Structure Recovered from a Single Camera, International Conference on Biometrics, Madrid, Spain, 2013.

Cited by

Metadata

Authors
Chakraborty, S., & Das, D.
Affiliations
National Institute Of Technology Silchar (IN)
Venue
International Journal on Information Theory
Published
2014-04-30
Volume
3
Issue
2
Pages
11-25
ISSN
  • 2319-7609 (ISSN-L)
  • 2320-8465
OpenAlex
W2897013524
Cited by
68
References
0
Citations by year
2026: 1 · 2025: 2 · 2024: 7 · 2023: 12 · 2022: 5 · 2021: 8 · 2020: 3 · 2019: 7 · 2018: 4 · 2017: 6 · 2016: 9 · 2015: 2 · 2014: 2
FWCI
8.10
Type
journal article
Language
en
Open access
Locations
  • International Journal on Information Theory (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
Keywords
face liveness detection, face recognition, spoofing attacks, anti-spoofing, biometric security, portrait photographs

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.