Multimodal face recognition method with two-dimensional hidden Markov model

Bulletin of the Polish Academy of Sciences. Technical Sciences

J. BobulskiInstitute of Computer and Information Science, Czestochowa University of Technology, 73 Dabrowskiego St., 42-201 Czestochowa, PolandEmailOther articles by this author:De Gruyter OnlineGoogle Scholar¹ 

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

关键词: Keywords: pattern recognition;    biometrics;    3D face recognition;    hidden Markov model;   

DOI  :  10.1515/bpasts-2017-0015

学科分类：工程和技术（综合）

来源: Polska Akademia Nauk * Centrum Upowszechniania Nauki / Polish Academy of Sciences, Center for the Advancement of Science

【 摘 要 】

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.

【 授权许可】

Unknown