Traffic Flow Background Detection Algorithm Based on Improved Gaussian Mixture Model

Abstract

Abstract: Aiming at the uniform characteristics of background pixels in traffic flow video, a spatial-temporal dual Gaussian mixture model background detection algorithm was proposed. Firstly the temporal Gauss mixture model was built to detect the background in temporal domain, and a double-threshold method was introduced to detect the background and foreground. When the detection result was uncertain, the spatial Gauss mixture model was built, and the spatial detection result was used to replace the temporal detection result. The experimental comparisons with different traffic flow video demonstrate that the proposed algorithm in this paper improves robustness in the initial stage and decreases the detection fault also when parking phenomenon occurrs.

Key words: traffic flow, video detection, spatialtemporal information, Gaussian mixture model, decision fusion

CLC Number:

LV　Fu-Qiang-1 , WANG Hui-1, LIU Hong-2. Traffic Flow Background Detection Algorithm Based on Improved Gaussian Mixture Model[J]. Journal of Shanghai Jiaotong University, 2012, 46(12): 1920-1925.

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