3D Face Recognition Using Geodesic PZM Array from a Single Model per Person

Title
3D Face Recognition Using Geodesic PZM Array from a Single Model per Person
Publication Date
2011-07
Author(s)
Hajati, Farshid
Raie, Abolghasem A
Gao, Yongsheng
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Place of publication
Japan
DOI
10.1587/transinf.e94.d.1488
UNE publication id
une:1959.11/70757
Abstract

For the 3D face recognition numerous methods have been proposed, but little attention has been given to the local-based representation for the texture map of the 3D models. In this paper, we propose a novel 3D face recognition approach based on locally extracted Geodesic Pseudo Zernike Moment Array (GPZMA) of the texture map when only one exemplar per person is available. In the proposed method, the function of the PZM is controlled by the geodesic deformations to tackle the problem of face recognition under the expression and pose variations. The feasibility and effectiveness investigation for the proposed method is conducted through a wide range of experiments using publicly available BU-3DFE and Bosphorus databases including samples with different expression and pose variations. The performance of the proposed method is compared with the performance of three state-of-the-art benchmark approaches. The encouraging experimental results demonstrate that the proposed method achieves much higher accuracy than the benchmarks in single-model databases.

Link
Citation
IEICE Transactions on Information and Systems, E94–D(7), p. 1488-1496
ISSN
1745-1361
0916-8532
Start page
1488
End page
1496

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