Pixel histogram based background modeling for moving target detection

Jiang Hua; Liangcai Zeng; Gongfa Li; Hongwei Wang; Zhaojie Ju

doi:10.1109/CcS49175.2020.9231352

Pixel histogram based background modeling for moving target detection

Jiang Hua
, Liangcai Zeng
, Gongfa Li
, Hongwei Wang
, Zhaojie Ju

Wuhan University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

176 Downloads (Pure)

Abstract

Existing moving target detection methods mainly include inter-frame differences, background differences, optical flow and so on. For the recognition of human motions in the process of human-computer collaboration, existing algorithms are usually difficult to meet the requirements of real-time processing and easily interfered by lighting or image noises. In this paper, a method for establishing a static background model based on pixel histogram is proposed. The effect of moving targets and noises on the background model is excluded due to the selectivity of the new algorithm to the gray values, so it can detect the real background more reliably. Compared with other moving target detection methods, this method has the characteristics of fast speed, strong anti-interference ability, and the ability to identify human body movement quickly and accurately.

Original language	English
Title of host publication	Proceedings of the 2020 International Symposium on Community-centric Systems (CcS)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	4
ISBN (Electronic)	978-1-7281-8741-9, 978-1-7281-8740-2
ISBN (Print)	978-1-7281-8742-6
DOIs	https://doi.org/10.1109/CcS49175.2020.9231352
Publication status	Published - 20 Oct 2020
Event	CcS 2020 International Symposium on Community-centric Systems - Tokyo, Japan Duration: 23 Sept 2020 → 26 Sept 2020

Conference

Conference	CcS 2020 International Symposium on Community-centric Systems
Country/Territory	Japan
City	Tokyo
Period	23/09/20 → 26/09/20

Keywords

noissn

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10.1109/CcS49175.2020.9231352

Postprint_CCS2020
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Accepted author manuscript (Post-print), 363 KB

Cite this

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title = "Pixel histogram based background modeling for moving target detection",

abstract = "Existing moving target detection methods mainly include inter-frame differences, background differences, optical flow and so on. For the recognition of human motions in the process of human-computer collaboration, existing algorithms are usually difficult to meet the requirements of real-time processing and easily interfered by lighting or image noises. In this paper, a method for establishing a static background model based on pixel histogram is proposed. The effect of moving targets and noises on the background model is excluded due to the selectivity of the new algorithm to the gray values, so it can detect the real background more reliably. Compared with other moving target detection methods, this method has the characteristics of fast speed, strong anti-interference ability, and the ability to identify human body movement quickly and accurately. ",

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author = "Jiang Hua and Liangcai Zeng and Gongfa Li and Hongwei Wang and Zhaojie Ju",

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booktitle = "Proceedings of the 2020 International Symposium on Community-centric Systems (CcS)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "CcS 2020 International Symposium on Community-centric Systems ; Conference date: 23-09-2020 Through 26-09-2020",

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Hua, J, Zeng, L, Li, G, Wang, H & Ju, Z 2020, Pixel histogram based background modeling for moving target detection. in Proceedings of the 2020 International Symposium on Community-centric Systems (CcS). Institute of Electrical and Electronics Engineers Inc., CcS 2020 International Symposium on Community-centric Systems, Tokyo, Japan, 23/09/20. https://doi.org/10.1109/CcS49175.2020.9231352

TY - GEN

T1 - Pixel histogram based background modeling for moving target detection

AU - Hua, Jiang

AU - Zeng, Liangcai

AU - Li, Gongfa

AU - Wang, Hongwei

AU - Ju, Zhaojie

PY - 2020/10/20

Y1 - 2020/10/20

N2 - Existing moving target detection methods mainly include inter-frame differences, background differences, optical flow and so on. For the recognition of human motions in the process of human-computer collaboration, existing algorithms are usually difficult to meet the requirements of real-time processing and easily interfered by lighting or image noises. In this paper, a method for establishing a static background model based on pixel histogram is proposed. The effect of moving targets and noises on the background model is excluded due to the selectivity of the new algorithm to the gray values, so it can detect the real background more reliably. Compared with other moving target detection methods, this method has the characteristics of fast speed, strong anti-interference ability, and the ability to identify human body movement quickly and accurately.

AB - Existing moving target detection methods mainly include inter-frame differences, background differences, optical flow and so on. For the recognition of human motions in the process of human-computer collaboration, existing algorithms are usually difficult to meet the requirements of real-time processing and easily interfered by lighting or image noises. In this paper, a method for establishing a static background model based on pixel histogram is proposed. The effect of moving targets and noises on the background model is excluded due to the selectivity of the new algorithm to the gray values, so it can detect the real background more reliably. Compared with other moving target detection methods, this method has the characteristics of fast speed, strong anti-interference ability, and the ability to identify human body movement quickly and accurately.

KW - noissn

UR - http://www.comp.sd.tmu.ac.jp/CcS2020/

U2 - 10.1109/CcS49175.2020.9231352

DO - 10.1109/CcS49175.2020.9231352

M3 - Conference contribution

SN - 978-1-7281-8742-6

BT - Proceedings of the 2020 International Symposium on Community-centric Systems (CcS)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - CcS 2020 International Symposium on Community-centric Systems

Y2 - 23 September 2020 through 26 September 2020

ER -

Pixel histogram based background modeling for moving target detection

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