@article {14,
	title = {Visual Workflow Recognition Using a Variational Bayesian Treatment of Multistream Fused Hidden Markov Models},
	journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
	volume = {22},
	year = {2012},
	month = {July},
	pages = {1076 -1086},
	keywords = {active learning-based visual workflow recognition, Bayes methods, classification variance, data labeling, hidden Markov models, image sequences, learned model, learning (artificial intelligence), maximum a posteriori training, maximum information gain method, maximum likelihood training, MFHMM parameters, model variance, multistream fused hidden Markov models, overfitting issues, point estimate-based methods, posterior distribution, training methods, unlabeled data, variational Bayesian treatment, video streaming, video surveillance},
	issn = {1051-8215},
	doi = {10.1109/TCSVT.2012.2189795},
	author = {Sotirios P. Chatzis and D. Kosmopoulos}
}
@article {24,
	title = {A variational Bayesian methodology for hidden Markov models utilizing Student{\textquoteright}s-t mixtures},
	journal = {Pattern Recognition},
	volume = {44},
	year = {2011},
	pages = {295 - 306},
	keywords = {Violence detection},
	issn = {0031-3203},
	doi = {10.1016/j.patcog.2010.09.001},
	author = {Sotirios P. Chatzis and D. Kosmopoulos}
}
@article {27,
	title = {Vision-based production of personalized video},
	journal = {Signal Processing: Image Communication},
	volume = {24},
	year = {2009},
	pages = {158 - 176},
	keywords = {Automated content production, Human identification, tracking},
	issn = {0923-5965},
	doi = {10.1016/j.image.2008.12.010},
	author = {D.I. Kosmopoulos and A. Doulamis and Makris, A. and N. Doulamis and Sotirios P. Chatzis and S.E. Middleton}
}
