Face Identification Using Large Feature Sets.

dc.creatorSchwartz, William Robson
dc.creatorGuo, Huimin
dc.creatorChoi, Jonghyun
dc.creatorDavis, Larry S
dc.date2012-Apr
dc.date2015-11-27T13:29:14Z
dc.date2015-11-27T13:29:14Z
dc.date.accessioned2018-03-29T01:16:48Z
dc.date.available2018-03-29T01:16:48Z
dc.identifierIeee Transactions On Image Processing : A Publication Of The Ieee Signal Processing Society. v. 21, n. 4, p. 2245-55, 2012-Apr.
dc.identifier1941-0042
dc.identifier10.1109/TIP.2011.2176951
dc.identifierhttp://www.ncbi.nlm.nih.gov/pubmed/22128005
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/200378
dc.identifier22128005
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1300611
dc.descriptionWith the goal of matching unknown faces against a gallery of known people, the face identification task has been studied for several decades. There are very accurate techniques to perform face identification in controlled environments, particularly when large numbers of samples are available for each face. However, face identification under uncontrolled environments or with a lack of training data is still an unsolved problem. We employ a large and rich set of feature descriptors (with more than 70,000 descriptors) for face identification using partial least squares to perform multichannel feature weighting. Then, we extend the method to a tree-based discriminative structure to reduce the time required to evaluate probe samples. The method is evaluated on Facial Recognition Technology (FERET) and Face Recognition Grand Challenge (FRGC) data sets. Experiments show that our identification method outperforms current state-of-the-art results, particularly for identifying faces acquired across varying conditions.
dc.description21
dc.description2245-55
dc.languageeng
dc.relationIeee Transactions On Image Processing : A Publication Of The Ieee Signal Processing Society
dc.relationIEEE Trans Image Process
dc.rightsfechado
dc.rights
dc.sourcePubMed
dc.subjectAlgorithms
dc.subjectArtificial Intelligence
dc.subjectBiometry
dc.subjectFace
dc.subjectHumans
dc.subjectImage Enhancement
dc.subjectImage Interpretation, Computer-assisted
dc.subjectInformation Storage And Retrieval
dc.subjectPattern Recognition, Automated
dc.subjectReproducibility Of Results
dc.subjectSensitivity And Specificity
dc.subjectSubtraction Technique
dc.titleFace Identification Using Large Feature Sets.
dc.typeArtículos de revistas


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