用单目无人机视频重建野生海豚3D形态与运动，实现体型自动评估。
Model-based Metric 3D Shape and Motion Reconstruction of Wild Bottlenose Dolphins in Drone-Shot Videos
- 基于物理模型+水下透射模型，处理水体遮挡问题。
- 在大体型海豚上优于人工测量，估算质量与体积更高效。
- 适合野外大规模监测，为保护研究提供自动化工具。
本文解决从单目无人机视频中估计野生海豚的度量三维形状与运动问题，旨在评估其身体状况。尽管陆地四足动物的三维重建已取得显著进展，但水生动物因自然水下环境观测困难仍缺乏研究。为此，我们提出一种基于模型的方法，引入水体透射模型以处理水下遮挡效应。该方法应用于不同海况下的视频数据，可估算海豚的质量与体积，并与基于人工2D测量的方法进行对比。此外，我们在已知真实质量的圈养海豚视频上验证了方法有效性。实验表明，虽然人工方法在多数情况下更精确，但在大型个体上本方法具有明显优势。结果表明，该方法具备规模化、自动化评估海豚体型的潜力。
原文摘要 · Abstract (English)
We address the problem of estimating the metric 3D shape and motion of wild dolphins from monocular video, with the aim of assessing their body condition. While considerable progress has been made in reconstructing 3D models of terrestrial quadrupeds, aquatic animals remain unexplored due to the difficulty of observing them in their natural underwater environment. To address this, we propose a model-based approach that incorporates a transmission model to account for water-induced occlusion. We apply our method to video captured under different sea conditions. We estimate mass and volume, and compare our results to a manual 2D measurements-based method. Additionally, we apply our method to video of captive animals with known ground truth mass. While in our experiments the manual approach is often more accurate, our method demonstrates a distinct advantage when applied to larger specimen. These findings highlight the potential of our method as a scalable and automated alternative for mass and volume estimation of dolphins from monocular video.
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