Indexación de Imágenes Faciales mediante Algoritmo basado en Permutaciones
Christian von Lucken$^{1}$, Liz González$^{1}$
$^{1}$Universidad Nacional de Asunción. Asunción Paraguay
Schedule:Wed 21st@15:15, Room: D

In face recognition systems that work with databases of thousands of images it is not practical to compare the query image against each image in the database to determine similarity. The increasing use of facial recognition in various fields and larger databases creates the need to explore mechanisms for efficient and effective search in terms of use of computing resources and percentage of hits. In order to ease the load of these systems and improve response time, several alternatives to reduce or eliminate the need for the exhaustive search of images were developed. Indexing methods are one of these alternatives. This paper presents a new indexing technique based on permutations, which in combination with a Principal Component Analysis algorithm, optimizes storage of images and accelerates the search process to predict the similarity between objects. The proposed method shows improved behaviour when compared against other techniques representing the state of the art using the FERET database.


	author 		= {Christian von Lucken and Liz González},
	title 		= {Indexación de Imágenes Faciales mediante Algoritmo basado en Permutaciones},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI)},
	pages 		= {1--10},
	year 		= {2015},
	editor 		= {Hector Cancela and Alex Cuadros-Vargas and Ernesto Cuadros-Vargas},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {},
	isbn 		= {978-1-4673-9143-6},

Generated by Ernesto Cuadros-Vargas , Sociedad Peruana de Computación-Peru, Universidad Católica San Pablo, Arequipa-Perú