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
Link To Document :
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