Face Recognition with 3D Face Asymmetry

Bobulski, Janusz

doi:10.1007/978-3-319-47274-4_6

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2017

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Cited by 1 publication

(2 citation statements)

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“…12. In comparison to other methods, there were achieved much better results, even than methods using three-dimensional data [11,40].…”

Section: Resultsmentioning

confidence: 85%

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The use of hidden Markov models to verify the identity based on facial asymmetry

Kubanek

Bobulski

2017

J Image Video Proc.

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This work concerns the use of biometric features, resulting from the look of a face, for the verification purposes. Different methods of selection and feature analysis during face recognition are presented here. The description contains mainly analysis possibilities and also identity verification based on asymmetric facial features-in later stages. The new verification method has been introduced based on designated characteristic points. These points were designated through appropriate coded information about facial asymmetry as observation vectors and recognition using hidden Markov models. The advantage of these models is that we can use vectors of different lengths. Such vectors appear in incomplete data when all points cannot be located.

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“…12. In comparison to other methods, there were achieved much better results, even than methods using three-dimensional data [11,40].…”

Section: Resultsmentioning

confidence: 85%

“…The important thing during extraction of these features is the choice of asymmetry line, and there are few ways to do this. Once the popular base on centre of the line connected inner eyes corner [11,12]. Next, the asymmetry measurement is calculated and used for identification.…”

Section: Introductionmentioning

confidence: 99%