5 papers · 1 filter
CHIRP dataset: towards long-term, individual-level, behavioral monitoring of bird populations in the wild
Alex Hoi Hang Chan, Neha Singhal, Onur Kocahan +6
Long-term behavioral monitoring of individual animals is crucial for studying behavioral changes that occur over different time scales, especially for conservation and evolutionary…
Towards Texture- And Shape-Independent 3D Keypoint Estimation in Birds
Valentin Schmuker, Alex Hoi Hang Chan, Bastian Goldluecke +1
In this paper, we present a texture-independent approach to estimate and track 3D joint positions of multiple pigeons. For this purpose, we build upon the existing 3D-MuPPET framew…
Towards Application-Specific Evaluation of Vision Models: Case Studies in Ecology and Biology
Alex Hoi Hang Chan, Otto Brookes, Urs Waldmann +11
Computer vision methods have demonstrated considerable potential to streamline ecological and biological workflows, with a growing number of datasets and models becoming available…
3D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking
Urs Waldmann, Alex Hoi Hang Chan, Hemal Naik +5
Markerless methods for animal posture tracking have been rapidly developing recently, but frameworks and benchmarks for tracking large animal groups in 3D are still lacking. To ove…
3D-POP -- An automated annotation approach to facilitate markerless 2D-3D tracking of freely moving birds with marker-based motion capture
Hemal Naik, Alex Hoi Hang Chan, Junran Yang +4
Recent advances in machine learning and computer vision are revolutionizing the field of animal behavior by enabling researchers to track the poses and locations of freely moving a…