The Application of Improved GG Clustering Algorithm in View-irrelevant Behavior Recognition

DOI

10.2991/ameii-15.2015.4How to use a DOI?

Keywords

GG clustering algorithm; Number of clusters; Cluster validity index; Behavior recognition.

Abstract

When cluster descriptors of behavior feature in the analyzing the behavior feature data of behavior under different view, the traditional FCM algorithm can not determine the number of clusters to the data with spherical structure, so this paper proposes an improved GG clustering algorithm to solve this problem. This algorithm determine the optimal cluster number by the indexes of inter-cluster compactness and the separation of clusters. Then model behavioral descriptors that have been clustered to reach the purpose of improving behavior recognition accuracy. The experimental results show that: the improved algorithm can classify and model behavioral descriptors better and improve the recognition accuracy.

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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TY  - CONF
AU  - Yun Liu
AU  - Jin Shao
AU  - Yan Yue
PY  - 2015/04
DA  - 2015/04
TI  - The Application of Improved GG Clustering Algorithm in View-irrelevant Behavior Recognition
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 22
EP  - 27
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.4
DO  - 10.2991/ameii-15.2015.4
ID  - Liu2015/04
ER  -