An online weight-based clustering algorithm for faces selection
Qianmu Li, Dayi Huang
Available Online May 2015.
- 10.2991/asei-15.2015.6How to use a DOI?
- online;weight;cluster;faces selection.
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.
- © 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 -