Moving objects detection algorithm of improved GMM based on 2-D entropy

DOI

10.2991/ifmeita-17.2018.69How to use a DOI?

Keywords

moving object detection; GMM; 2-D entropy; learning rate

Abstract

Aiming at the background updating slow in Gaussian mixture model in abrupt illumination, 2-D entropy is used to judge the mutation of light, thus changing the learning rate so as to speed up the background modeling. The experimental results show that the method can make the background more accurate in complex scenes, and improve the accuracy of target detection.

Copyright

© 2018, 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  - Gang Feng
PY  - 2018/02
DA  - 2018/02
TI  - Moving objects detection algorithm of improved GMM based on 2-D entropy
BT  - Proceedings of the 2nd International Forum on Management, Education and Information Technology Application (IFMEITA 2017)
PB  - Atlantis Press
SP  - 411
EP  - 415
SN  - 2352-5398
UR  - https://doi.org/10.2991/ifmeita-17.2018.69
DO  - 10.2991/ifmeita-17.2018.69
ID  - Feng2018/02
ER  -