Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/19527
Título: ENCARA2: real-time detection of multiple faces at different resolutions in video streams
Autores/as: Castrillón, M. 
Déniz Suárez,Oscar 
Guerra Artal, Cayetano Nicolás 
Hernández, M. 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Tracking
Fecha de publicación: 2007
Publicación seriada: Journal of Visual Communication and Image Representation 
Resumen: This paper describes a face detection system which goes beyond traditional face detection approaches normally designed for still images. The system described in this paper has been designed taking into account the temporal coherence contained in a video stream in order to build a robust detector. Multiple and real-time detection is achieved by means of cue combination. The resulting system builds a feature based model for each detected face, and searches them using the various model information in the next frame.
The experiments have been focused on video streams, where our system can actually exploit the bene ts of the temporal coherence integration. The results achieved for video stream processing outperform Rowley-Kanade''s and Viola-Jones'' solutions providing eye and face data in real-time with a notable correct detection rate, aprox. 99:9% faces and 87:5% eye pairs on 26338 images.
URI: http://hdl.handle.net/10553/19527
ISSN: 1047-3203
DOI: 10.1016/j.jvcir.2006.11.004
Fuente: Journal of Visual Communication and Image Representation [ISSN 1047-3203], v. 18, p. 130-140
Colección:Artículos
miniatura
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