I-MuPPET: Interactive Multi-Pigeon Pose Estimation and Tracking (Dataset)

Kurzanzeige
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dc.contributor.authorWaldmann, Urs
dc.contributor.authorNaik, Hemal
dc.contributor.authorNagy, Mate
dc.contributor.authorKano, Fumihiro
dc.contributor.authorCouzin, Iain D.
dc.contributor.authorDeussen, Oliver
dc.contributor.authorGoldlücke, Bastian
dc.date.accessioned2025-04-02T09:11:38Z
dc.date.available2025-04-02T09:11:38Z
dc.date.created2023-05-31T09:37:59.000Z
dc.date.issued2023
dc.description.abstractThis data entry contains the annotated single pigeon data from the I-MuPPET GCPR 2022 paper. This data contains our annotated single pigeon data with RGB images and seven distinct keypoint annotations. The experiments were carried out by Hemal Naik, Máté Nagy, Fumihiro Kano and Iain D. Couzin and were approved by the Regierungspräsidium Freiburg under the permit number Az. 35-9185.81/G-19/107. Data was recorded by two Vicon Vue 2 cameras (1920x1080 pixels) at 50 Hz, four Vantage 5 and 26 Vero 2.2 sensors. The dataset was originally created during the Ph.D. thesis work of Hemal Naik. The method to reproduce the setup and dataset can be found at https://mediatum.ub.tum.de/?id=1554403. An updated version of this dataset with 4K resolution (3D-POP) is available at https://doi.org/10.17617/3.HPBBC7. The code base is available at https://github.com/alexhang212/dataset-3dpop. The users can reproduce annotations or improve them by adding more key points. Code for I-MuPPET available at https://github.com/urs-waldmann/i-muppet/.
dc.description.versionpublisheddeu
dc.identifier.doi10.5281/zenodo.7989830
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/72870
dc.language.isoeng
dc.rightsCreative Commons Attribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/legalcode
dc.subjectpose estimation
dc.subjectdeep learning
dc.subjectpigeons
dc.subject.ddc004
dc.titleI-MuPPET: Interactive Multi-Pigeon Pose Estimation and Tracking (Dataset)eng
dspace.entity.typeDataset
kops.citation.bibtex
kops.citation.iso690WALDMANN,  Urs,  Hemal NAIK,  Mate NAGY,  Fumihiro KANO,  Iain D. COUZIN,  Oliver DEUSSEN,  Bastian GOLDLÜCKE, 2023. I-MuPPET: Interactive Multi-Pigeon Pose Estimation and Tracking (Dataset)deu
kops.citation.iso690WALDMANN,  Urs,  Hemal NAIK,  Mate NAGY,  Fumihiro KANO,  Iain D. COUZIN,  Oliver DEUSSEN,  Bastian GOLDLÜCKE, 2023. I-MuPPET: Interactive Multi-Pigeon Pose Estimation and Tracking (Dataset)eng
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