DocumentCode
2017187
Title
Moving Object Extraction in Complex Scenes
Author
Fan, Sicun ; Liu, Zhijing
Author_Institution
Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´´an
Volume
2
fYear
2008
fDate
17-18 Oct. 2008
Firstpage
126
Lastpage
129
Abstract
Moving object detection plays an important roll in intelligent monitor system; it may have a direct influence on the final detection result. In this paper, a self-adaptive system of moving object detection based on Gaussian mixture models (GMM) is designed, and this method can reduce some unfavorable influences, such as weather or lighting changes. Moreover, this paper modifies the algorithm of combination of background subtraction method and temporal differencing method, makes the contour of moving object more precise and removes environmental noise points effectively. Many experiments on outdoor video streams are tested and the results have shown that this method gives stable performance and good robustness.
Keywords
Gaussian distribution; edge detection; image denoising; image sequences; motion estimation; object detection; video signal processing; Gaussian distribution mixture model; background subtraction method; complex scene; environmental noise removal; intelligent video monitor system; moving object contour extraction; moving object detection; outdoor video stream; self-adaptive system; temporal differencing method; Computational intelligence; Computer science; Computerized monitoring; Data mining; Gaussian distribution; Image motion analysis; Intelligent systems; Layout; Object detection; Optical filters; Gaussian Mixture Models; background subtraction method; moving object extraction;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3311-7
Type
conf
DOI
10.1109/ISCID.2008.168
Filename
4725473
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