Thermal face recognition using local patterns

Gabriel Hermosilla, Gonzalo Farias, Hector Vargas, Francisco Gallardo, Cesar San-Martin

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

The aim of this article is to compare the performance of well-known visible recognition methods but using the thermal spectrum. Specifically, the work considers two local-matching based methods for face recognition commonly used in visible spectrum: Local Binary Pattern (LBP) and Local Derivative Pattern (LDP). The methods are evaluated and compared using the UCHThermalFace database, which includes evaluation methodology that considers real-world conditions. The comparative study results shown that, contrary to what happens in the visible spectrum, the LBP method obtains the best results from the thermal face recognition. On the other hand, LDP results show that it is not an appropriate descriptor for face recognition systems in the thermal spectrum.

Idioma originalInglés
Título de la publicación alojadaProgress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings
EditoresEduardo Bayro-Corrochano, Edwin Hancock
EditorialSpringer Verlag
Páginas486-497
Número de páginas12
ISBN (versión digital)9783319125671
DOI
EstadoPublicada - 2014
Publicado de forma externa
Evento19th Iberoamerican Congress on Pattern Recognition, CIARP 2014 - Puerto Vallarta, México
Duración: 2 nov. 20145 nov. 2014

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen8827
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
País/TerritorioMéxico
CiudadPuerto Vallarta
Período2/11/145/11/14

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