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We implement a system for vehicle detection and tracking from traffic video using Gaussian mixture models and Bayesian estimation. The system provides robust foreground segmentation of moving vehicles through a K-means clustering approximation as well as vehicle tracking correspondence between frames by correlating Kalman and particle filters.