Face recognition using a hybrid SVM–LBP approach and the Indian movie face database

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/69524
Información del item - Informació de l'item - Item information
Title: Face recognition using a hybrid SVM–LBP approach and the Indian movie face database
Authors: Pujol, Francisco A. | Jimeno-Morenilla, Antonio | Sanchez-Romero, Jose-Luis
Research Group/s: UniCAD: Grupo de investigación en CAD/CAM/CAE de la Universidad de Alicante
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Keywords: Face recognition | Hybrid methods | Local binary patterns | Support vector machines
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: 10-Sep-2017
Publisher: Current Science Association
Citation: Current Science. 2017, 113(5): 974-977. doi:10.18520/cs/v113/i05/974-977
Abstract: Local binary patterns (LBP) are an effective texture descriptor for face recognition. In this work, a LBP-based hybrid system for face recognition is proposed. Thus, the dimensionality of LBP histograms is reduced by using principal component analysis and the classification is performed with support vector machines. The experiments were completed using the challenging Indian Movie Face Database and show that our method achieves high recognition rates while reducing 95% the dimensions of the original LBP histograms. Moreover, our algorithm is compared against some state-of-the-art approaches. The results indicate that our method outperforms other approaches, with accurate face recognition results.
URI: http://hdl.handle.net/10045/69524
ISSN: 0011-3891
DOI: 10.18520/cs/v113/i05/974-977
Language: eng
Type: info:eu-repo/semantics/article
Rights: © Current Science Association
Peer Review: si
Publisher version: http://dx.doi.org/10.18520/cs/v113/i05/974-977
Appears in Collections:INV - UNICAD - Artículos de Revistas

Files in This Item:
Files in This Item:
File Description SizeFormat 
Thumbnail2017_Pujol_etal_CurrentSci.pdf3,08 MBAdobe PDFOpen Preview


Items in RUA are protected by copyright, with all rights reserved, unless otherwise indicated.