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dc.contributor.authorMåløy, Håkon
dc.contributor.authorAamodt, Agnar
dc.contributor.authorMisimi, Ekrem
dc.description.abstractRecent developments have shown that Deep Learning approaches are well suited for Human Action Recognition. On the other hand, the application of deep learning for action or behaviour recognition in other domains such as animal or livestock is comparatively limited. Action recognition in fish is a particularly challenging task due to specific research challenges such as the lack of distinct poses in fish behavior and the capture of spatio-temporal changes. Action recognition of salmon is valuable in relation to managing and optimizing many aquaculture operations today such as feeding, as one of the most costly operations in aquaculture. Inspired by these application domains and research challenges we introduce a deep video classification network for action recognition of salmon from underwater videos. We propose a Dual-Stream Recurrent Network (DSRN) to automatically capture the spatio-temporal behavior of salmon during swimming. The DSRN combines the spatial and motion-temporal information through the use of a spatial network, a 3D-convolutional motion network and a LSTM recurrent classification network. The DSRN shows an accuracy that is suitable for industrial use in prediction of salmon behavior with a prediction accuracy of 80%, validated on the task of predicting Feeding and NonFeeding behavior in salmon at a real fish farm during production. Our results show that the DSRN architecture has high potential in feeding action recognition for salmon in aquaculture and for applications domains lacking distinct poses and with dynamic spatio-temporal changes.nb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.subjectFish action/behaviour recognitionnb_NO
dc.subjectFish feedingnb_NO
dc.subjectConvolutional neural networknb_NO
dc.subjectRecurrent neural networknb_NO
dc.subjectAction recognitionnb_NO
dc.subjectVideo analysisnb_NO
dc.subjectOptical flownb_NO
dc.titleA spatio-temporal recurrent network for salmon feeding action recognition from underwater videos in aquaculturenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.rights.holder© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY licensenb_NO
dc.source.journalComputers and Electronics in Agriculturenb_NO

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Navngivelse 4.0 Internasjonal
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