@article {123,
	title = {A top-down event-driven approach for concurrent activity recognition},
	journal = {Multimedia Tools Appl.},
	volume = {69},
	year = {2014},
	pages = {293-311},
	abstract = {<p><span>In this paper a framework for automatic online workflow recognition in industrial environments where the issue of concurrent activities rises, is presented. The framework consists of three main parts: The first part is devoted to detecting activity in specific Regions of Interest (ROIs) of the video sequence. This is effected by separating each frame into ROIs and representing the resulting subimages through feature vectors. By observing these vectors we can determine when there is action in a particular ROI. The second part of the framework lies in examining whether the detected activity corresponds to a workflow related event. This is accomplished by HMM modeling. Finally, the third part employs a string matching based technique to confirm the validity of the observed sequence of events or correct any detection or classification errors. This last step also addresses a top down approach by informing lower system levels (such as image representation or object tracking) about the errors committed. The performance of the proposed approach is thoroughly evaluated under real-life complex visual workflow understanding scenarios, in an industrial plant. The obtained results are compared and discussed.</span></p>},
	keywords = {Concurrent activity recognition Event detection Top-down Region of interest (ROI) Workflow},
	author = {Athanasios Voulodimos and Dimitrios I. Kosmopoulos and Nikolaos D. Doulamis and Theodora A. Varvarigou}
}
@article {21,
	title = {A Threefold Dataset for Activity and Workflow Recognition in Complex Industrial Environments},
	journal = {MultiMedia, IEEE},
	volume = {19},
	year = {2012},
	month = {July-Sept.},
	pages = {42 -52},
	issn = {1070-986X},
	doi = {10.1109/MMUL.2012.31},
	author = {Athanasios Voulodimos and D. Kosmopoulos and Vasileiou, Georgios and Sardis, Emmanuel and Anagnostopoulos, Vasileios and Lalos, Constantinos and Doulamis, A.D. and Varvarigou, T.A.}
}
@article {9,
	title = {Online classification of visual tasks for industrial workflow monitoring},
	journal = {Neural Networks},
	volume = {24},
	year = {2011},
	pages = {852{\textendash}860},
	keywords = {Activity recognition, ESN, Fusion, Genetic algorithm, HMM, Workflow},
	issn = {0893-6080},
	author = {Athanasios Voulodimos and D. Kosmopoulos and Veres, Galina and Helmut Grabner and Van Gool, Luc and Varvarigou, T.A.}
}
@proceedings {8,
	title = {Robust Workflow Recognition Using Holistic Features and Outlier-Tolerant Fused Hidden Markov Models},
	journal = {International Conference on Artificial Neural Networks},
	volume = {1},
	year = {2010},
	pages = {551-560},
	author = {Athanasios Voulodimos and Helmut Grabner and D. Kosmopoulos and Van Gool, Luc and Varvarigou, T.A.}
}
