A combination of spatiotemporal ica and euclidean features for face recognition

ICA decomposes a set of features into a basis whose components are statistically independent. It minimizes the statistical dependence between basis functions and searches for a linear transformation to express a set of features as a linear combination of statistically independent basis functions. Th...

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Detalles Bibliográficos
Autores principales: Lei, Jiajin, Weiland, Chris, Lu, Chao, Lay, Tim
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2006
Materias:
Ciencias Informáticas
machine vision
face recognition
spatiotemporal ICA
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23953
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23953
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
machine vision
face recognition
spatiotemporal ICA
spellingShingle Ciencias Informáticas
machine vision
face recognition
spatiotemporal ICA
Lei, Jiajin
Weiland, Chris
Lu, Chao
Lay, Tim
A combination of spatiotemporal ica and euclidean features for face recognition
topic_facet Ciencias Informáticas
machine vision
face recognition
spatiotemporal ICA
description ICA decomposes a set of features into a basis whose components are statistically independent. It minimizes the statistical dependence between basis functions and searches for a linear transformation to express a set of features as a linear combination of statistically independent basis functions. Though ICA has found its application in face recognition, mostly spatial ICA was employed. Recently, we studied a joint spatial and temporal ICA method, and compared the performance of different ICA approaches by using our special face database collected by AcSys FRS Discovery system. In our study, we have found that spatiotemporal ICA apparently outperforms spatial ICA, and it can be much more robust with better performance than spatial ICA. These findings justify the promise of spatiotemporal ICA for face recognition. In this paper we report our progress and explore the possible combination of the Euclidean distance features and the ICA features to maximize the success rate of face recognition
format Objeto de conferencia
Objeto de conferencia
author Lei, Jiajin
Weiland, Chris
Lu, Chao
Lay, Tim
author_facet Lei, Jiajin
Weiland, Chris
Lu, Chao
Lay, Tim
author_sort Lei, Jiajin
title A combination of spatiotemporal ica and euclidean features for face recognition
title_short A combination of spatiotemporal ica and euclidean features for face recognition
title_full A combination of spatiotemporal ica and euclidean features for face recognition
title_fullStr A combination of spatiotemporal ica and euclidean features for face recognition
title_full_unstemmed A combination of spatiotemporal ica and euclidean features for face recognition
title_sort combination of spatiotemporal ica and euclidean features for face recognition
publishDate 2006
url http://sedici.unlp.edu.ar/handle/10915/23953
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