Proceedings of the 2015 International conference on Applied Science and Engineering Innovation

An online weight-based clustering algorithm for faces selection

Authors
Qianmu Li, Dayi Huang
Corresponding Author
Qianmu Li
Available Online May 2015.
DOI
10.2991/asei-15.2015.6How to use a DOI?
Keywords
online;weight;cluster;faces selection.
Abstract

With the scale of the application of face recognition getting bigger and bigger, A thinking of selecting faces as a preprocessing has conducted on how to improve the system’s efficiency. After summarized and analyzed such a thinking, this paper has discussed the pros and cons of face data clustering by using the traditional K-means clustering algorithm. In addition, this paper has further proposed an online weight-based clustering algorithm (OWCA for short) that strengthens the advantages of face data clustering, restricts the computational complexity and develops an online processing scheme. Experimental results on the ORL face library demonstrated the correctness and effectiveness of OWCA.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
Series
Advances in Engineering Research
Publication Date
May 2015
ISBN
978-94-62520-94-3
ISSN
2352-5401
DOI
10.2991/asei-15.2015.6How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Qianmu Li
AU  - Dayi Huang
PY  - 2015/05
DA  - 2015/05
TI  - An online weight-based clustering algorithm for faces selection
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 24
EP  - 30
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.6
DO  - 10.2991/asei-15.2015.6
ID  - Li2015/05
ER  -