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Tools for semi-automatic monitoring of industrial workflows

Tools for semi-automatic monitoring of industrial workflows
Tools for semi-automatic monitoring of industrial workflows
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 pre-recorded and analyzed footage from multiple cameras in order to get a comprehensive overview of the workflows. Furthermore, the tools help technical administrators in adjusting algorithms by letting the user correct detections (for relevance feedback) and ground truth for evaluation. Another important feature of the tool chain is the capability to inform the employees about potentially risky conditions using the tool for automatic detection of unusual scenes
computer vision, industrial environments, applications, human detection and tracking, workflow recognition
Veres, Galina
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Middleton, Lee
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Sabeur, Zoheir
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Bouchrika, Imed
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Arbab-Zavar, Banafshe
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Carter, John
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Nixon, Mark
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Grabner, Helmut
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Stalder, Severin
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Van Gool, Luc
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Morzinger, Roland
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Thaler, Marcus
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Rene, Schuster
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Albert, Hofman
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Thallinger, Georg
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Veres, Galina
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Middleton, Lee
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Sabeur, Zoheir
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Bouchrika, Imed
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Arbab-Zavar, Banafshe
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Carter, John
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Nixon, Mark
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Grabner, Helmut
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Stalder, Severin
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Van Gool, Luc
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Morzinger, Roland
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Thaler, Marcus
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Rene, Schuster
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Albert, Hofman
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Thallinger, Georg
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Veres, Galina, Middleton, Lee, Sabeur, Zoheir, Bouchrika, Imed, Arbab-Zavar, Banafshe, Carter, John, Nixon, Mark, Grabner, Helmut, Stalder, Severin, Van Gool, Luc, Morzinger, Roland, Thaler, Marcus, Rene, Schuster, Albert, Hofman and Thallinger, Georg (2010) Tools for semi-automatic monitoring of industrial workflows. ACM Multimedia 2010, Italy. 25 - 29 Oct 2010.

Record type: Conference or Workshop Item (Paper)

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 pre-recorded and analyzed footage from multiple cameras in order to get a comprehensive overview of the workflows. Furthermore, the tools help technical administrators in adjusting algorithms by letting the user correct detections (for relevance feedback) and ground truth for evaluation. Another important feature of the tool chain is the capability to inform the employees about potentially risky conditions using the tool for automatic detection of unusual scenes

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More information

Published date: October 2010
Venue - Dates: ACM Multimedia 2010, Italy, 2010-10-25 - 2010-10-29
Keywords: computer vision, industrial environments, applications, human detection and tracking, workflow recognition
Organisations: Southampton Wireless Group, IT Innovation

Identifiers

Local EPrints ID: 272321
URI: http://eprints.soton.ac.uk/id/eprint/272321
PURE UUID: 1d15ba49-f010-4f4a-a39c-bcced2a442f3
ORCID for Zoheir Sabeur: ORCID iD orcid.org/0000-0003-4325-4871
ORCID for Mark Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 24 May 2011 13:22
Last modified: 20 Jul 2019 01:28

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Contributors

Author: Galina Veres
Author: Lee Middleton
Author: Zoheir Sabeur ORCID iD
Author: Imed Bouchrika
Author: Banafshe Arbab-Zavar
Author: John Carter
Author: Mark Nixon ORCID iD
Author: Helmut Grabner
Author: Severin Stalder
Author: Luc Van Gool
Author: Roland Morzinger
Author: Marcus Thaler
Author: Schuster Rene
Author: Hofman Albert
Author: Georg Thallinger

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