Linear Prediction Based Mixture Models for Event Detection in Video Sequences

Dierck Matern, Alexandru Paul Condurache, Alfred Mertins

Abstract

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.
Original languageEnglish
Title of host publicationPattern Recognition and Image Analysis
EditorsJordi Vitrià, João Miguel Sanches, Mario Hernández
Number of pages8
Volume6669
Place of PublicationBerlin, Heidelberg
PublisherSpringer Berlin Heidelberg
Publication date01.06.2011
Pages25-32
ISBN (Print)978-3-642-21256-7
ISBN (Electronic)978-3-642-21257-4
DOIs
Publication statusPublished - 01.06.2011
Event5th Iberian Conference on Pattern Recognition and Image Analysis - Las Palmas de Gran Canaria, Spain
Duration: 08.06.201110.06.2011
Conference number: 85429

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