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Authors: Xiaolong Wang 1 ; Vincent Ly 1 ; Rui Guo 2 and Chandra Kambhamettu 1

Affiliations: 1 University of Delaware, United States ; 2 The University of Tennessee, United States

Keyword(s): Restricted Boltzmann Machines, Canonical Correlation Analysis, Heterogeneous Face Recognition, Matching, Feature Extraction.

Abstract: This paper proposes a new scheme for the 2D-3D face recognition problem. Our proposed framework mainly consists of Restricted Boltzmann Machines (RBMs) and a correlation learning model. In the framework, a single-layer network based on RBMs is adopted to extract latent features over two different modalities. Furthermore, the latent hidden layer features of different models are projected to formulate a shared space based on correlation learning. Then several different correlation learning schemes are evaluated against the proposed scheme. We evaluate the advocated approach on a popular face dataset-FRGCV2.0. Experimental results demonstrate that the latent features extracted using RBMs are effective in improving the performance of correlation mapping for 2D-3D face recognition.

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Paper citation in several formats:
Wang, X.; Ly, V.; Guo, R. and Kambhamettu, C. (2014). 2D-3D Face Recognition via Restricted Boltzmann Machines. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP; ISBN 978-989-758-004-8; ISSN 2184-4321, SciTePress, pages 574-580. DOI: 10.5220/0004736505740580

@conference{visapp14,
author={Xiaolong Wang. and Vincent Ly. and Rui Guo. and Chandra Kambhamettu.},
title={2D-3D Face Recognition via Restricted Boltzmann Machines},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={574-580},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004736505740580},
isbn={978-989-758-004-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP
TI - 2D-3D Face Recognition via Restricted Boltzmann Machines
SN - 978-989-758-004-8
IS - 2184-4321
AU - Wang, X.
AU - Ly, V.
AU - Guo, R.
AU - Kambhamettu, C.
PY - 2014
SP - 574
EP - 580
DO - 10.5220/0004736505740580
PB - SciTePress

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