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Face Description with Local Binary Patterns: Application to Face Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence · 2006 · Vol. 28(12) · pp. 2037–2041
Timo AhonenAbdenour HadidMatti Pietikäinen

Abstract

This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features. The face image is divided into several regions from which the LBP feature distributions are extracted and concatenated into an enhanced feature vector to be used as a face descriptor. The performance of the proposed method is assessed in the face recognition problem under different challenges. Other applications and several extensions are also discussed.

Face and Expression RecognitionImage Retrieval and Classification TechniquesAdvanced Image and Video Retrieval TechniquesLocal binary patternsArtificial intelligencePattern recognition (psychology)Facial recognition systemComputer scienceFace (sociological concept)Feature (linguistics)Computer visionFeature extractionThree-dimensional face recognition

MeSH terms

AlgorithmsArtificial IntelligenceBiometryFaceHumansImage EnhancementImage Interpretation, Computer-AssistedNumerical Analysis, Computer-AssistedPattern Recognition, AutomatedSensitivity and SpecificitySignal Processing, Computer-AssistedReproducibility of ResultsInformation Storage and Retrieval

Funding

  • Academy of Finland
Citations
5,587
FWCI
60.63
field-weighted impact
References
34
Percentile
100%
vs. same field & year
Citations per year
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References
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Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
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IEEE Transactions on Pattern Analysis and Machine Intelligence · 2005 · 6,699 citations
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