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- W2356841116 abstract "Background model is a common method for detecting moving object in traffic surveillance video.The effect of Gaussian Mixture Model used in training background model is good,but its convergence velocity is low.At present,many improved models only accelerate the initial convergent velocity.For accelerating the convergent velocity when background changes in the process of surveillance,the models need to detect whether background has changed or not real time and then to be initialized again if background changes.In this paper we put forward a new improved Gaussian Mixture Model,which needn't be initialized again if background information changes and avoids redundant steps of detecting whether background has changed or not real time.Experiment result of the new model shows the convergent velocity in the process of surveillance is improved evidently." @default.
- W2356841116 created "2016-06-24" @default.
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- W2356841116 date "2008-01-01" @default.
- W2356841116 modified "2023-09-24" @default.
- W2356841116 title "A Fast Convergent Gaussian Mixture Model for Moving Object Detection" @default.
- W2356841116 hasPublicationYear "2008" @default.
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