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), Queenstown, New Zealand, 10 - 12 Nov 2010.
PDF (conference paper)
- Accepted Version
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.
|Item Type:||Conference or Workshop Item (Speech)|
|Additional Information:||Event Dates: 10-12 Novermber|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > IT Innovation Centre
|Date Deposited:||17 Feb 2011 11:24|
|Last Modified:||27 Mar 2014 20:17|
|Further Information:||Google Scholar|
|ISI Citation Count:||0|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)