Multimodal Face Biometrics by Using Convolutional Neural Networks

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Biometric recognition is one of the major challenging topics which needs high performance of recognition accuracy. Most of existing methods rely on a single source of biometric to achieve recognition. The recognition accuracy in biometrics is affected by the variability of effects, including illumination and appearance variations. In this paper, we propose a new multimodal biometrics recognition using convolutional neural network. We focus on multimodal biometrics from face and periocular regions. Through experiments, we have demonstrated that facial multimodal biometrics features deep learning framework is helpful for achieving high recognition performance.
Publisher
한국멀티미디어학회
Issue Date
2017-02
Language
English
Keywords

Multimodal Biometrics Recognition; Face Recognition; Convolutional Neural Networks

Citation

멀티미디어학회논문지, v.20, no.2, pp.170 - 178

ISSN
1229-7771
URI
http://hdl.handle.net/10203/225350
Appears in Collection
EE-Journal Papers(저널논문)
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