An improved Gaussian mixture model

Dayong Gong; Zhihua Wang

doi:10.1117/12.2010876

14 March 2013 An improved Gaussian mixture model

Dayong Gong, Zhihua Wang

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87682C (2013) https://doi.org/10.1117/12.2010876
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

An improved Gaussian mixture model is presented to substitute the typical method of Chris Stauffer which revealed its weakness in uncontrollability of the background constructing course and foreground mergence time as well as invalidation to the low duty background. By setting appropriate time parameters which meet the monitoring needs, the improved method effectively controls the estimates updating process of each background in Gaussian mixture model via layered attenuating the estimates and intensifying the recurrence events while requires almost the same computation. The simulation of traffic monitoring videos indicates that: this model has no scraps of provisionally staying objects, efficaciously picks up the low duty background.

Citation Download Citation

Dayong Gong and Zhihua Wang "An improved Gaussian mixture model", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87682C (14 March 2013); https://doi.org/10.1117/12.2010876

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