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This 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/.
pigeons, deep learning, pose estimation
pigeons, deep learning, pose estimation
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