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dc.date.accessioned 2012-07-12T15:32:10Z
dc.date.available 2012-07-12T15:32:10Z
dc.date.issued 2011
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/18622
dc.description.abstract In this paper, a strategy for face recognition based on SIFT descriptors of the images involved is presented. In order to reduce the number of false positives and computation time, a selection of the most representative feature descriptors is carried out by applying a variation of the binary PSO method. This version improves its operation by a suitable positioning of the velocity vector. To achieve this, a new modified version of the continuous gBest PSO algorithm is used. The results obtained allow stating that the descriptors can be successfully selected through the strategy proposed solving the problems initially mentioned. en
dc.format.extent 111-120 es
dc.language en es
dc.subject face recognition; SIFT descriptors; swarm intelligence; binary PSO; velocity control es
dc.title Face recognition using SIFT descriptors and binary PSO with velocity control es
dc.type Objeto de conferencia es
sedici.creator.person Maulini, Juan Andrés es
sedici.creator.person Lanzarini, Laura Cristina es
sedici.description.note Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2011-10
sedici.relation.event XVII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)