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- Title
Local Comparative Decimal Pattern for Face Recognition.
- Authors
Tabejamaat, Mohsen; Mousavi, Abdolmajid; Gavrilova, Marina L.
- Abstract
Rapid growth of social networks has provided an extraordinary medium to share a large volume of photographs online. This calls for designing efficient face recognition techniques that are applicable to images with low resolutions and arbitrary poses. This paper proposes a new pose invariant face recognition method for low resolution images using only a single training sample. A 3D model, reconstructed using Generic Elastic Model (3D GEM) from a frontal view training sample, is used to generate a set of nonfrontal gallery face images. The face region of the nonfrontal query sample is then extracted using the same landmark detection technique as in the 3D GEM algorithm. Afterwards, a novel texture representation technique called Local Comparative Decimal Pattern (LCDP) is proposed to extract features from each of the training and query samples. A set of experimental results on the ORL, Georgia Tech (GT), and LFW face databases demonstrates the efficiency of the proposed method compared to other state-of-the-art approaches.
- Subjects
HUMAN facial recognition software; SOCIAL networks; ALGORITHMS
- Publication
International Journal of Pattern Recognition & Artificial Intelligence, 2020, Vol 34, Issue 12, pN.PAG
- ISSN
0218-0014
- Publication type
Article
- DOI
10.1142/S0218001420560066