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Code for "Learning methods for dynamic topic modeling in automated behavior analysis"

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posted on 2018-01-08, 11:33 authored by Olga IsupovaOlga Isupova, Danil Kuzin, Lyudmila MihaylovaLyudmila Mihaylova

This is source code for the algorithms presented in the paper "Learning Methods for Dynamic Topic Modeling in Automated Behavior Analysis" by Olga Isupova, Danil Kuzin, Lyudmila Mihaylova. Published in IEEE Transactions on Neural Networks and Learning Systems, 2017. DOI: 10.1109/TNNLS.2017.2735364.

Two learning methods for the Markov Clustering Topic Model (MCTM) are developed - Expectation-Maximisation (EM) algorithm and Variational Bayes (VB) inference.

Implementation is done in Matlab.

Funding

Bayesian Tracking and Reasoning over Time under Grant EP/K021516/1 and EC Seventh Framework Programme [FP7 2013-2017] TRAcking in compleX sensor systems under Grant 607400

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Keywords

Video analytics Behavior analysis Learning dynamic models Unsupervised learning Expectation maximisation Variational Bayesian approach Computer Engineering

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GPL 2.0+

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