Tools for semi-automatic monitoring of industrial workflows

Mörzinger, R; Sardis, M; Rosenberg, I; Grabner, H; Veres, G; Bouchrika, I; Thaler, M; Schuster, R; Hofmann, A; Thallinger, G; Anagnostopoulos, V; Kosmopoulos, D; Voulodimos, A; Lalos, C; Doulamis, N; Varvarigou, T; Zelada, R; Soler, I; Stalder, S; Gool, L; Middleton, L; Sabeur, Z; Arbab-Zavar, B; Carter, J; Nixon, M

dc.contributor.author	Mörzinger, R	en
dc.contributor.author	Sardis, M	en
dc.contributor.author	Rosenberg, I	en
dc.contributor.author	Grabner, H	en
dc.contributor.author	Veres, G	en
dc.contributor.author	Bouchrika, I	en
dc.contributor.author	Thaler, M	en
dc.contributor.author	Schuster, R	en
dc.contributor.author	Hofmann, A	en
dc.contributor.author	Thallinger, G	en
dc.contributor.author	Anagnostopoulos, V	en
dc.contributor.author	Kosmopoulos, D	en
dc.contributor.author	Voulodimos, A	en
dc.contributor.author	Lalos, C	en
dc.contributor.author	Doulamis, N	en
dc.contributor.author	Varvarigou, T	en
dc.contributor.author	Zelada, R	en
dc.contributor.author	Soler, I	en
dc.contributor.author	Stalder, S	en
dc.contributor.author	Gool, L	en
dc.contributor.author	Middleton, L	en
dc.contributor.author	Sabeur, Z	en
dc.contributor.author	Arbab-Zavar, B	en
dc.contributor.author	Carter, J	en
dc.contributor.author	Nixon, M	en
dc.date.accessioned	2014-03-01T01:59:34Z
dc.date.available	2014-03-01T01:59:34Z
dc.date.issued	2010	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/28980
dc.subject	Automatic Detection	en
dc.subject	Computer Vision	en
dc.subject	Relevance Feedback	en
dc.subject	Ground Truth	en
dc.title	Tools for semi-automatic monitoring of industrial workflows	en
heal.type	journalArticle	en
heal.identifier.primary	10.1145/1877868.1877889	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1877868.1877889	en
heal.publicationDate	2010	en
heal.abstract	This paper describes a tool chain for monitoring complex workflows. Statistics obtained from automatic workflow monitoring in a car assembly environment assist in improving industrial safety and process quality. To this end, we propose automatic detection and tracking of humans and their activity in multiple networked cameras. The described tools offer human operators retrospective analysis of a huge amount of	en
dc.identifier.doi	10.1145/1877868.1877889	en