On the Complementarity of Face Parts for Gender Recognition
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comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/159830
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Title
On the Complementarity of Face Parts for Gender RecognitionDate
2008Publisher
Springer VerlagISBN
978-3-540-85920-8ISSN
03029743Bibliographic citation
Andreu Y., Mollineda R.A. (2008) On the Complementarity of Face Parts for Gender Recognition. In: Ruiz-Shulcloper J., Kropatsch W.G. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2008. Lecture Notes in Computer Science, vol 5197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85920-8_31Type
info:eu-repo/semantics/conferenceObjectVersion
info:eu-repo/semantics/acceptedVersionAbstract
This paper evaluates the expected complementarity between
the most prominent parts of the face for the gender recognition task.
Given the image of a face, five important parts (right and left eyes, nose,
mouth and ... [+]
This paper evaluates the expected complementarity between
the most prominent parts of the face for the gender recognition task.
Given the image of a face, five important parts (right and left eyes, nose,
mouth and chin) are extracted and represented as appearance-based data
vectors. In addition, the full face and its internal rectangular region (excluding
hair, ears and contour) are also coded. Several mixtures of classifiers
based on (subsets of) these five single parts were designed using simple
voting, weighted voting and other learner as combiners. Experiments
using the FERET database prove that ensembles perform significantly
better than plain classifiers based on single parts (as expected). [-]
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Lecture notes in computer science; 5197Rights
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess