Temporally-consistent 3D Reconstruction of Birds
<|reference_start|>Temporally-consistent 3D Reconstruction of Birds: This paper deals with 3D reconstruction of seabirds which recently came into focus of environmental scientists as valuable bio-indicators for environmental change. Such 3D information is beneficial for analyzing the bird's behavior and physiological shape, for example by tracking motion, shape, and appearance changes. From a computer vision perspective birds are especially challenging due to their rapid and oftentimes non-rigid motions. We propose an approach to reconstruct the 3D pose and shape from monocular videos of a specific breed of seabird - the common murre. Our approach comprises a full pipeline of detection, tracking, segmentation, and temporally consistent 3D reconstruction. Additionally, we propose a temporal loss that extends current single-image 3D bird pose estimators to the temporal domain. Moreover, we provide a real-world dataset of 10000 frames of video observations on average capture nine birds simultaneously, comprising a large variety of motions and interactions, including a smaller test set with bird-specific keypoint labels. Using our temporal optimization, we achieve state-of-the-art performance for the challenging sequences in our dataset.<|reference_end|>
@article{hägerlind2024temporally-consistent,
    title={Temporally-consistent 3D Reconstruction of Birds},
    author={Johannes H"agerlind, Jonas Hentati-Sundberg, Bastian Wandt},
    journal={arXiv preprint arXiv:2408.13629},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.13629},
    primaryClass={cs.CV}
}