Worgan, SF, Behera, A, Cohn, AG et al. (1 more author) (2011) Exploiting petri-net structure for activity classification and user instruction within an industrial setting. In: ICMI'11 - Proceedings of the 2011 ACM International Conference on Multimodal Interaction. International Conference on Multimodal Interaction 2011, Alicante, Spain. ACM , 113 - 120 . ISBN 978-1-4503-0641-6
Abstract
Live workflow monitoring and the resulting user interaction in industrial settings faces a number of challenges. A formal workflow may be unknown or implicit, data may be sparse and certain isolated actions may be undetectable given current visual feature extraction technology. This paper attempts to address these problems by inducing a structural workflow model from multiple expert demonstrations. When interacting with a naive user, this workflow is combined with spatial and temporal information, under a Bayesian framework, to give appropriate feedback and instruction. Structural information is captured by translating a Markov chain of actions into a simple place/transition petri-net. This novel petri-net structure maintains a continuous record of the current workbench configuration and allows multiple sub-sequences to be monitored without resorting to second order processes. This allows the user to switch between multiple sub-tasks, while still receiving informative feedback from the system. As this model captures the complete workflow, human inspection of safety critical processes and expert annotation of user instructions can be made. Activity classification and user instruction results show a significant on-line performance improvement when compared to the existing Hidden Markov Model or pLSA based state of the art. Further analysis reveals that the majority of our model's classification errors are caused by small de-synchronisation events rather than significant workflow deviations. We conclude with a discussion of the generalisability of the induced place/transition petri-net to other activity recognition tasks and summarise the developments of this model.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Apr 2013 14:13 |
Last Modified: | 04 Nov 2016 02:42 |
Published Version: | http://dx.doi.org/10.1145/2070481.2070502 |
Status: | Published |
Publisher: | ACM |
Identification Number: | 10.1145/2070481.2070502 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:75457 |