In this paper, we propose a method for the detection of irregularities in time series, based on linear prediction. We demonstrate how we can estimate the linear predictor by solving the Yule Walker equations, and how we can combine several predictors in a simple mixture model. In several tests, we compare our model to a Gaussian mixture and a hidden Markov model approach. We successfully apply our method to event detection in a video sequence. © 2011 Springer-Verlag.
CITATION STYLE
Matern, D., Condurache, A. P., & Mertins, A. (2011). Linear prediction based mixture models for event detection in video sequences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6669 LNCS, pp. 25–32). https://doi.org/10.1007/978-3-642-21257-4_4
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