Variational Inference for Background Subtraction in Infrared Imagery


We propose a Gaussian mixture model for background subtraction in infrared imagery. Following a Bayesian approach, our method automatically estimates the number of Gaussian components as well as their parameters, while simultaneously it avoids over/under fitting. The equations for estimating model parameters are analytically derived and thus our method does… (More)
DOI: 10.1007/978-3-319-27857-5_62

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