3D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single View.
3D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single View.
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DOI：
10.1007/978-3-030-58523-5_1
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发表时间：
2020
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影响因子：
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通讯作者：
Daniilidis, Kostas
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作者：
Badger, Marc;Wang, Yufu;Modh, Adarsh;Perkes, Ammon;Kolotouros, Nikos;Pfrommer, Bernd G;Schmidt, Marc F;Daniilidis, Kostas
动物姿势的自动捕捉正在改变我们研究神经科学和社会行为的方式。动作携带着重要的社会线索，但目前的方法无法可靠地估计动物的姿势和形状，特别是对于像鸟类这样的社会动物，它们经常被彼此和环境中的物体遮挡。为了解决这个问题，我们首先引入了一种模型和多视图优化方法，我们使用它来捕获活鸟显示的独特形状和姿态空间。然后，我们介绍了关键点，面具，姿势和形状回归的管道和实验，从单个视图恢复准确的鸟类姿势。最后，我们提供了广泛的多视图关键点和掩码注释，这些注释来自一组15只群居鸟类，它们一起住在室外鸟舍中。该项目网站上有视频、结果、代码、网格模型和宾夕法尼亚大学鸟类研究所数据集，可在https://marcbadger.github.io/avian-mesh上找到。
Automated capture of animal pose is transforming how we study neuroscience and social behavior. Movements carry important social cues, but current methods are not able to robustly estimate pose and shape of animals, particularly for social animals such as birds, which are often occluded by each other and objects in the environment. To address this problem, we first introduce a model and multi-view optimization approach, which we use to capture the unique shape and pose space displayed by live birds. We then introduce a pipeline and experiments for keypoint, mask, pose, and shape regression that recovers accurate avian postures from single views. Finally, we provide extensive multi-view keypoint and mask annotations collected from a group of 15 social birds housed together in an outdoor aviary. The project website with videos, results, code, mesh model, and the Penn Aviary Dataset can be found at https://marcbadger.github.io/avian-mesh.