Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015

Online K-Means Algorithm for Background Subtraction

Authors
Peng Chen, Beibei Jin, Xiangbing Zhu, Mingxing Fang
Corresponding Author
Peng Chen
Available Online December 2015.
DOI
https://doi.org/10.2991/icmmcce-15.2015.137How to use a DOI?
Keywords
Gaussian mixture model; on-line K-means; background subtraction
Abstract
Background subtraction is an important step in video processing. GMM algorithm uses Gaussian mixture model to identify moving objects and efficient equations have been derived to update GMM parameters. In order to compute parameters more accurately while maintain constant computing time per frame, we apply online K-Means algorithm to update the parameters of Gaussian mixture models and the corresponding incremental K-means equations are derived. Experiments demonstrate that online K-means algorithm can give more efficient segment result than previous update equations.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
Part of series
Advances in Computer Science Research
Publication Date
December 2015
ISBN
978-94-6252-133-9
DOI
https://doi.org/10.2991/icmmcce-15.2015.137How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Peng Chen
AU  - Beibei Jin
AU  - Xiangbing Zhu
AU  - Mingxing Fang
PY  - 2015/12
DA  - 2015/12
TI  - Online K-Means Algorithm for Background Subtraction
BT  - 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
PB  - Atlantis Press
UR  - https://doi.org/10.2991/icmmcce-15.2015.137
DO  - https://doi.org/10.2991/icmmcce-15.2015.137
ID  - Chen2015/12
ER  -