Improved Moving Target Detection Based on Multi-Model Mean Model

被引:1
作者
Wang, Weiwei [1 ]
Gao, Deyong [1 ]
Wang, Yangping [2 ,3 ]
Gao, Decheng [4 ]
机构
[1] Lanzhou Jiaotong Univ, Sch Elect & Informat Engn, Lanzhou, Gansu, Peoples R China
[2] Gansu Prov Engn Res Ctr Artificial Intelligence &, Lanzhou, Gansu, Peoples R China
[3] Gansu Prov Key Lab Syst Dynam & Reliabil Rail Tra, Lanzhou, Gansu, Peoples R China
[4] Gansu Inst Metrol, Lanzhou, Gansu, Peoples R China
来源
2018 4TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND MATERIAL APPLICATION | 2019年 / 252卷
基金
中国国家自然科学基金;
关键词
D O I
10.1088/1755-1315/252/5/052134
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Aiming at the problem of low detection accuracy of multi-mode mean model in complex scenarios, an improved detection method of moving target based on multi-mode mean model is proposed.Firstly, the background model is constructed using the multi-mode mean value model.According to different scene information, different thresholds are set and adjusted adaptively.The foreground image obtained by background difference method is detected by frame difference method, and the experiment is compared and analyzed.The detection rate and the error rate are reduced, and the detection accuracy is improved. Finally, the simulation results of three-segment video verify the effectiveness of the proposed method.
引用
收藏
页数:7
相关论文
共 50 条
[21]   Skill transfer improved with a multi-model approach [J].
Nakawaki, DE ;
Joo, S ;
Miyazaki, F .
ADVANCED ROBOTICS, 2000, 14 (05) :371-375
[22]   An intelligent detection method for assembly based on multi-model cascade [J].
Xu, Hanzhong ;
Wu, Dianliang ;
Zou, Kai ;
Yu, Qihang ;
Yu, Haiwen .
2024 16TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING, ICMLC 2024, 2024, :280-286
[23]   Foreground object detection based on multi-model background maintenance [J].
Tsai, Tsung-Han ;
Sheu, Wen-Tsai ;
Lin, Chung-Yuan .
ISM WORKSHOPS 2007: NINTH IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA - WORKSHOPS, PROCEEDINGS, 2007, :151-158
[24]   Pathogenic virus detection method based on multi-model fusion [J].
Zhao, Xiaoyong ;
Wang, Jingwei .
PROCEEDINGS OF THE 2020 INTERNATIONAL CONFERENCE ON COMPUTER, INFORMATION AND TELECOMMUNICATION SYSTEMS (CITS), 2020, :89-92
[25]   Fake User Detection Based on Multi-Model Joint Representation [J].
Li, Jun ;
Jiang, Wentao ;
Zhang, Jianyi ;
Shao, Yanhua ;
Zhu, Wei .
INFORMATION, 2024, 15 (05)
[26]   A multi-model approach to the detection of web-based attacks [J].
Kruegel, C ;
Vigna, G ;
Robertson, W .
COMPUTER NETWORKS, 2005, 48 (05) :717-738
[27]   Improved Multi-Model Classification Technique for Sound Event Detection in Urban Environments [J].
Khan, Muhammad Salman ;
Shah, Mohsin ;
Khan, Asfandyar ;
Aldweesh, Amjad ;
Ali, Mushtaq ;
Eldin, Elsayed Tag ;
Ishaq, Waqar ;
Hussain, Lal .
APPLIED SCIENCES-BASEL, 2022, 12 (19)
[28]   Multi-algorithm and multi-model based drug target prediction and web server [J].
Ying-tao Liu ;
Yi Li ;
Zi-fu Huang ;
Zhi-jian Xu ;
Zhuo Yang ;
Zhu-xi Chen ;
Kai-xian Chen ;
Ji-ye Shi ;
Wei-liang Zhu .
Acta Pharmacologica Sinica, 2014, 35 :419-431
[29]   Multi-algorithm and multi-model based drug target prediction and web server [J].
Liu, Ying-tao ;
Li, Yi ;
Huang, Zi-fu ;
Xu, Zhi-jian ;
Yang, Zhuo ;
Chen, Zhu-xi ;
Chen, Kai-xian ;
Shi, Ji-ye ;
Zhu, Wei-liang .
ACTA PHARMACOLOGICA SINICA, 2014, 35 (03) :419-431
[30]   Moving Target Detection Algorithm Based on Gaussian Mixture Model [J].
Wang, Zhihua ;
Kai, Du ;
Zhang, Xiandong .
FIFTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2013), 2013, 8878