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Automatic Workflow Monitoring in Industrial Environments

Veres, Galina, Grabner, Helmut, Middleton, Lee and Van Gool, Luc (2010) Automatic Workflow Monitoring in Industrial Environments At Asian Conference on computer Vision (ACCV), New Zealand. 10 - 12 Nov 2010.

Record type: Conference or Workshop Item (Other)


Robust automatic workflow monitoring using visual sensors in industrial environments is still an unsolved problem. This is mainly due to the difficulties of recording data in work settings and the environmental conditions (large occlusions, similar background/foreground) which do not allow object detection/tracking algorithms to perform robustly. Hence approaches analysing trajectories are limited in such environments. However, workflow monitoring is especially needed due to quality and safety requirements. In this paper we propose a robust approach for workflow classification in industrial environments. The proposed approach consists of a robust scene descriptor and an efficient time series analysis method. Experimental results on a challenging car manufacturing dataset showed that the proposed scene descriptor is able to detect both human and machinery related motion robustly and the used time series analysis method can classify tasks in a given workflow automatically.

PDF 135_finalpaper.pdf - Accepted Manuscript
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Accepted/In Press date: November 2010
Additional Information: Event Dates: 10-12 Novermber
Venue - Dates: Asian Conference on computer Vision (ACCV), New Zealand, 2010-11-10 - 2010-11-12
Organisations: Electronics & Computer Science, IT Innovation


Local EPrints ID: 272039
PURE UUID: 6252e2e8-9545-4ac2-87a2-db1d26b0ec16

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Date deposited: 17 Feb 2011 11:24
Last modified: 18 Jul 2017 06:35

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Author: Galina Veres
Author: Helmut Grabner
Author: Lee Middleton
Author: Luc Van Gool

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