Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/16403
| Título: | A study for the self similarity smile detection | Autores/as: | Freire-Obregón, David Antón Canalís, Luis Castrillón, Modesto |
Clasificación UNESCO: | 120304 Inteligencia artificial | Palabras clave: | Classification | Fecha de publicación: | 2009 | Publicación seriada: | Lecture Notes in Computer Science | Conferencia: | Joint International Conference on Biometric ID Management and Multimodal Communication (BioID-MultiComm) Joint COST 2101 and 2102 International Conference on Biometric ID Management and Multimodal Communication, BioID_MultiComm 2009 |
Resumen: | This work makes an extensive experimental study of smile detection testing the Local Binary Patterns (LBP) combined with self similarity (LAC) as main descriptors of the image, along with the powerful Support Vector Machines classifier. Results show that error rates can be acceptable and the self similarity approach for the detection of smiles is suitable for real-time interaction, although there is still room for improvement. | URI: | http://hdl.handle.net/10553/16403 | ISBN: | 978-3-642-04390-1 3642043909 |
ISSN: | 0302-9743 | DOI: | 10.1007/978-3-642-04391-8_13 | Fuente: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 5707 LNCS, p. 97-104 |
| Colección: | Actas de congresos |
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