Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42867
Título: Face and facial feature detection evaluation. Performance evaluation of public domain haar detectors for face and facial feature detection
Autores/as: Castrillón-Santana, M. 
Déniz-Suárez, O.
Antón-Canalís, L.
Lorenzo-Navarro, J. 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Face and facial feature detection
Haar wavelets
Human computer interaction
Fecha de publicación: 2008
Proyectos: Tecnicas Para El Robustecimiento de Procesos en Vision Artificial Para la Interaccion 
Conferencia: 3rd International Conference on Computer Vision Theory and Applications 
Resumen: Fast and reliable face and facial feature detection are required abilities for any Human Computer Interaction approach based on Computer Vision. Since the publication of the Viola-Jones object detection framework and the more recent open source implementation, an increasing number of applications have appeared, particularly in the context of facial processing. In this respect, the OpenCV community shares a collection of public domain classifiers for this scenario. However, as far as we know these classifiers have never been evaluated and/or compared. In this paper we analyze the individual performance of all those public classifiers getting the best performance for each target. These results are valid to define a baseline for future approaches. Additionally we propose a simple hierarchical combination of those classifiers to increase the facial feature detection rate while reducing the face false detection rate.
URI: http://hdl.handle.net/10553/42867
ISBN: 978-989-8111-21-0
DOI: 10.5220/0001073101670172
Fuente: Visapp 2008: Proceedings Of The Third International Conference On Computer Vision Theory And Applications, Vol 2, p. 167-172, (2008)
Colección:Actas de congresos
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