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Cited by 677

The DOI matches its Crossref record; 151 of the 151 references it cites were found in a registry or an index.

A Survey of Face Recognition Techniques

Open access
Jafri, Rabia, Arabnia, Hamid R.·2009·Journal of Information Processing Systems
DOI 10.3745/jips.2009.5.2.041
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Abstract

Face recognition presents a challenging problem in the field of image analysis and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. Face recognition techniques can be broadly divided into three categories based on the face data acquisition methodology: methods that operate on intensity images; those that deal with video sequences; and those that require other sensory data such as 3D information or infra-red imagery. In this paper, an overview of some of the well-known methods in each of these categories is provided and some of the benefits and drawbacks of the schemes mentioned therein are examined. Furthermore, a discussion outlining the incentive for using face recognition, the applications of this technology, and some of the difficulties plaguing current systems with regard to this task has also been provided. This paper also mentions some of the most recent algorithms developed for this purpose and attempts to give an idea of the state of the art of face recognition technology.

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Show all 151 references

Research works printed but not linked: 42

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Metadata

Authors
Jafri, R., & Arabnia, H. R.
Venue
Journal of Information Processing Systems
Publisher
Korea Information Processing Society
Published
2009-06-30
Volume
5
Issue
2
Pages
41-68
ISSN
1976-913X (ISSN-L)
DOI
10.3745/jips.2009.5.2.041
OpenAlex
W1999533590
Cited by
677
References
151
FWCI
12.09
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A Survey of Face Recognition Techniques. https://app.cochat.ai/papers/10.3745/jips.2009.5.2.041
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Jafri, R., & Arabnia, H. R. (2009). A Survey of Face Recognition Techniques. Journal of Information Processing Systems. https://doi.org/10.3745/jips.2009.5.2.041

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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.