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A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps

In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Loc...

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Detalles Bibliográficos
Autores principales: Yin, Shouyi, Dai, Xu, Ouyang, Peng, Liu, Leibo, Wei, Shaojun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239878/
https://www.ncbi.nlm.nih.gov/pubmed/25333290
http://dx.doi.org/10.3390/s141019561
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author Yin, Shouyi
Dai, Xu
Ouyang, Peng
Liu, Leibo
Wei, Shaojun
author_facet Yin, Shouyi
Dai, Xu
Ouyang, Peng
Liu, Leibo
Wei, Shaojun
author_sort Yin, Shouyi
collection PubMed
description In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features.
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spelling pubmed-42398782014-11-21 A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps Yin, Shouyi Dai, Xu Ouyang, Peng Liu, Leibo Wei, Shaojun Sensors (Basel) Article In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features. MDPI 2014-10-20 /pmc/articles/PMC4239878/ /pubmed/25333290 http://dx.doi.org/10.3390/s141019561 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yin, Shouyi
Dai, Xu
Ouyang, Peng
Liu, Leibo
Wei, Shaojun
A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps
title A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps
title_full A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps
title_fullStr A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps
title_full_unstemmed A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps
title_short A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps
title_sort multi-modal face recognition method using complete local derivative patterns and depth maps
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239878/
https://www.ncbi.nlm.nih.gov/pubmed/25333290
http://dx.doi.org/10.3390/s141019561
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