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DC poleHodnotaJazyk
dc.contributor.authorFang, Lintao
dc.contributor.authorAlbadawi, Mohamad
dc.contributor.authorDolereit, Tim
dc.contributor.authorKuijper, Arjan
dc.contributor.authorMatthias, Vahl
dc.contributor.editorSkala, Václav
dc.date.accessioned2024-07-21T08:53:07Z-
dc.date.available2024-07-21T08:53:07Z-
dc.date.issued2024-
dc.identifier.citationJournal of WSCG. 2024, vol. 32, no. 1-2, p. 51-60.en
dc.identifier.issn1213 – 6972
dc.identifier.issn1213 – 6980 (CD-ROM)
dc.identifier.issn1213 – 6964 (on-line)
dc.identifier.urihttp://hdl.handle.net/11025/57344
dc.description.sponsorshipThis project was funded by the Federal Ministry of Education and Research under the funding code 03ZU1107MB.cs_CZ
dc.description.sponsorshipThis project was funded by the Federal Ministry of Education and Research under the funding code 03ZU1107MB.en
dc.format10 s.cs_CZ
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.rights© Václav Skala - UNION Agencycs_CZ
dc.rights© Václav Skala - UNION Agencyen
dc.subjectindex aktivity rybcs
dc.subjectsledování více objektůcs
dc.subjectrekonstrukce mapy absolutní hloubkycs
dc.subjectpost-processingový přístupcs
dc.subjectodhad pohybucs
dc.subjectrybí rojcs
dc.titleFish Motion Estimation Using ML-based Relative Depth Estimation and Multi-Object Trackingen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersion-
dc.description.abstract-translatedFish motion is a very important indicator of various health conditions of fish swarms in the fish farming industry. Many researchers have successfully analyzed fish motion information with the help of special sensors or computer vision, but their research results were either limited to few robotic fishes for ground-truth reasons or restricted to 2D space. Therefore, there is still a lack of methods that can accurately estimate the motion of a real fish swarm in 3D space. Here we present our Fish Motion Estimation (FME) algorithm that uses multi-object tracking, monocular depth estimation, and our novel post-processing approach to estimate fish motion in the world coordinate system. Our results show that the estimated fish motion approximates the ground truth very well and the achieved accuracy of 81.0% is sufficient for the use case of fish monitoring in fish farmsen
dc.subject.translatedfish activity indexen
dc.subject.translatedmulti-object trackingen
dc.subject.translatedabsolute depth map reconstructionen
dc.subject.translatedpost-processing approachen
dc.subject.translatedmotion estimationen
dc.subject.translatedfish swarmen
dc.identifier.doihttps://www.doi.org/10.24132/JWSCG.2024.6
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Volume 32, number 1-2 (2024)

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  1. DSpace at University of West Bohemia
  2. Publikace ZČU / UWB Publications
  3. Časopisy ZČU / UWB Journals
  4. Journal of WSCG
  5. Volume 32 (2024)
  6. Volume 32, number 1-2 (2024)