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3D-POP - An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture
May 7, 2024
Naik, Hemal; Chan, Alex Hoi Hang; Yang, Junran; Delacoux, Mathilde; Couzin, D. Iain; Kano, Fumihiro; Nagy, Mate, 2023, "3D-POP - An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture", https://doi.org/10.17617/3.HPBBC7, Edmond, V6
The 3DPOP dataset is a large scale 2D to 3D posture, identity and trajectory dataset for freely moving pigeons. We use marker-based motion tracking to first track precise head and body position and orientation for multiple individuals, then propagated custom keypoints based on th...
Wild-MuPPET - Multi-view posture dataset of foraging pigeons in the wild
Jan 3, 2024
Waldmann, Urs; Chan, Hoi Hang Alex; Naik, Hemal; Nagy, Mate; Couzin, Iain D.; Deussen, Oliver; Goldluecke, Bastian; Kano, Fumihiro, 2024, "Wild-MuPPET - Multi-view posture dataset of foraging pigeons in the wild", https://doi.org/10.17617/3.ENDMTI, Edmond, V1
Wild-MuPPET is a multi-view posture dataset of foraging pigeons outdoors, with 500 frames of 3D-ground truth and 2000 frames of 2D-ground truth of 9 keypoints. Paper: https://doi.org/10.48550/arXiv.2308.15316 Git repository: https://github.com/alexhang212/3D-MuPPET
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