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Neural Processing Letters

Erschienen in:

01.02.2014

Face Recognition and Micro-expression Recognition Based on Discriminant Tensor Subspace Analysis Plus Extreme Learning Machine

verfasst von: Su-Jing Wang, Hui-Ling Chen, Wen-Jing Yan, Yu-Hsin Chen, Xiaolan Fu

Erschienen in: Neural Processing Letters | Ausgabe 1/2014

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Abstract

In this paper, a novel recognition algorithm based on discriminant tensor subspace analysis (DTSA) and extreme learning machine (ELM) is introduced. DTSA treats a gray facial image as a second order tensor and adopts two-sided transformations to reduce dimensionality. One of the many advantages of DTSA is its ability to preserve the spatial structure information of the images. In order to deal with micro-expression video clips, we extend DTSA to a high-order tensor. Discriminative features are generated using DTSA to further enhance the classification performance of ELM classifier. Another notable contribution of the proposed method includes significant improvements in face and micro-expression recognition accuracy. The experimental results on the ORL, Yale, YaleB facial databases and CASME micro-expression database show the effectiveness of the proposed method.

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The matlab code can be downloaded from http://www.zjucadcg.cn/dengcai/Data/data.html.

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Titel: Face Recognition and Micro-expression Recognition Based on Discriminant Tensor Subspace Analysis Plus Extreme Learning Machine
verfasst von: Su-Jing Wang
Hui-Ling Chen
Wen-Jing Yan
Yu-Hsin Chen
Xiaolan Fu
Publikationsdatum: 01.02.2014
Verlag: Springer US
Erschienen in: Neural Processing Letters / Ausgabe 1/2014
Print ISSN: 1370-4621
Elektronische ISSN: 1573-773X
DOI: https://doi.org/10.1007/s11063-013-9288-7

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