IEICE TRANSACTIONS on Information
Moving Object Detection Based on Clausius Entropy
Summary :
This paper proposes a novel image segmentation method based on Clausius entropy and adaptive Gaussian mixture model for detecting moving objects in a complex environment. The results suggest that the proposed method performs better than existing methods in extracting the foreground in various video sequences composed of multiple objects, lighting reflections, and background clutter.
- Publication
- IEICE TRANSACTIONS on Information Vol.E94-D No.2 pp.388-391
- Publication Date
- 2011/02/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E94.D.388
- Type of Manuscript
- LETTER
- Category
- Image Recognition, Computer Vision
Authors
Keyword
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Jonghyun PARK, Wanhyun CHO, Gueesang LEE, Soonyoung PARK, "Moving Object Detection Based on Clausius Entropy" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 2, pp. 388-391, February 2011, doi: 10.1587/transinf.E94.D.388.
Abstract: This paper proposes a novel image segmentation method based on Clausius entropy and adaptive Gaussian mixture model for detecting moving objects in a complex environment. The results suggest that the proposed method performs better than existing methods in extracting the foreground in various video sequences composed of multiple objects, lighting reflections, and background clutter.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.388/_p
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@ARTICLE{e94-d_2_388,
author={Jonghyun PARK, Wanhyun CHO, Gueesang LEE, Soonyoung PARK, },
journal={IEICE TRANSACTIONS on Information},
title={Moving Object Detection Based on Clausius Entropy},
year={2011},
volume={E94-D},
number={2},
pages={388-391},
abstract={This paper proposes a novel image segmentation method based on Clausius entropy and adaptive Gaussian mixture model for detecting moving objects in a complex environment. The results suggest that the proposed method performs better than existing methods in extracting the foreground in various video sequences composed of multiple objects, lighting reflections, and background clutter.},
keywords={},
doi={10.1587/transinf.E94.D.388},
ISSN={1745-1361},
month={February},}
Copy
TY - JOUR
TI - Moving Object Detection Based on Clausius Entropy
T2 - IEICE TRANSACTIONS on Information
SP - 388
EP - 391
AU - Jonghyun PARK
AU - Wanhyun CHO
AU - Gueesang LEE
AU - Soonyoung PARK
PY - 2011
DO - 10.1587/transinf.E94.D.388
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2011
AB - This paper proposes a novel image segmentation method based on Clausius entropy and adaptive Gaussian mixture model for detecting moving objects in a complex environment. The results suggest that the proposed method performs better than existing methods in extracting the foreground in various video sequences composed of multiple objects, lighting reflections, and background clutter.
ER -
English
