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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 |