Open Systems for Online Face Recognition. Furht, B., editor In Encyclopedia of Multimedia, pages 692–693. Springer US, 2008. 00000![Open Systems for Online Face Recognition [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex DefinitionAs opposed to the traditional supervised learning approach, online approaches using unsupervised learning techniques have been explored for online face recognition.Generic person identification is important for novel applications such as video news library and continuous lifelog video. Face recognition technology has seen significant advances, and the FERET evaluation program has created sound testing methodologies [1]. In spite of these advances, face recognition to date, remains a very hard problem. As opposed to the traditional supervised learning approach, online approaches using unsupervised learning techniques have been explored. In [2], authors investigate such an “open” system based on eigenfaces and clustering techniques that allows a humanoid robot to automatically learn the faces of people it interacts with. In [3], authors describe an algorithm that uses virtual labels created from clustering in the output space (name or gender of a person) to incrementa ...
@incollection{furht_open_2008,
title = {Open {Systems} for {Online} {Face} {Recognition}},
copyright = {©2008 Springer-Verlag},
isbn = {978-0-387-74724-8 978-0-387-78414-4},
url = {http://link.springer.com/referenceworkentry/10.1007/978-0-387-78414-4_170},
abstract = {DefinitionAs opposed to the traditional supervised learning approach, online approaches using unsupervised learning techniques have been explored for online face recognition.Generic person identification is important for novel applications such as video news library and continuous lifelog video. Face recognition technology has seen significant advances, and the FERET evaluation program has created sound testing methodologies [1]. In spite of these advances, face recognition to date, remains a very hard problem. As opposed to the traditional supervised learning approach, online approaches using unsupervised learning techniques have been explored. In [2], authors investigate such an “open” system based on eigenfaces and clustering techniques that allows a humanoid robot to automatically learn the faces of people it interacts with. In [3], authors describe an algorithm that uses virtual labels created from clustering in the output space (name or gender of a person) to incrementa ...},
language = {en},
urldate = {2016-05-03},
booktitle = {Encyclopedia of {Multimedia}},
publisher = {Springer US},
editor = {Furht, Borko},
year = {2008},
note = {00000},
pages = {692--693}
}
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