A Low Illumination Environment Motion Detection Method based on Dictionary Learning

Huaxin Xiao, Yu Liu, Bin Wang, Shuren Tan, Maojun Zhang

Abstract

This paper proposes a dictionary-based motion detection method on video images captured under low light with serious noise. The proposed approach trains a dictionary by background images without foreground. It then reconstructs the test image according to the theory of sparse coding, and introduces the Structural Similarity Index Measurement (SSIM) as the detection standard to identify the detection caused by the brightness and contrast ratio changes. Experimental results show that compared to the mixture of Gaussian model and ViBe method, the proposed method can reach a better result under extreme low illumination circumstance.

References

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Paper Citation


in Harvard Style

Xiao H., Liu Y., Wang B., Tan S. and Zhang M. (2014). A Low Illumination Environment Motion Detection Method based on Dictionary Learning . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 147-154. DOI: 10.5220/0004753701470154


in Bibtex Style

@conference{icpram14,
author={Huaxin Xiao and Yu Liu and Bin Wang and Shuren Tan and Maojun Zhang},
title={A Low Illumination Environment Motion Detection Method based on Dictionary Learning},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={147-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004753701470154},
isbn={978-989-758-018-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A Low Illumination Environment Motion Detection Method based on Dictionary Learning
SN - 978-989-758-018-5
AU - Xiao H.
AU - Liu Y.
AU - Wang B.
AU - Tan S.
AU - Zhang M.
PY - 2014
SP - 147
EP - 154
DO - 10.5220/0004753701470154