Multimodal face recognition method with two-dimensional hidden Markov model

• Autorzy: Bobulski J.

Identyfikatory

DOI

10.1515/bpasts-2017-0015

• Języki publikacji: EN

Abstrakty

EN

The paper presents a new solution for the face recognition based on two-dimensional hidden Markov models. The traditional HMM uses one-dimensional data vectors, which is a drawback in the case of 2D and 3D image processing, because part of the information is lost during the conversion to one-dimensional features vector. The paper presents a concept of the full ergodic 2DHMM, which can be used in 2D and 3D face recognition. The experimental results demonstrate that the system based on two dimensional hidden Markov models is able to achieve a good recognition rate for 2D, 3D and multimodal (2D+3D) face images recognition, and is faster than ICP method.

Słowa kluczowe

EN

pattern recognition; biometrics; 3D face recognition; hidden Markov model

PL

rozpoznawanie wzorców; biometria; rozpoznawanie twarzy 3D; ukryty model Markowa

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2017
• Tom: Vol. 65, nr 1
• Strony: 121—128
• Opis fizyczny: Bibliogr. 35 poz., tab., rys., wykr., fot.

Twórcy

autor

Bobulski J.

• Institute of Computer and Information Science, Czestochowa University of Technology, 73 Dabrowskiego St., 42-201 Czestochowa, Poland

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).