STARFLAG集体动物行为手册：第一部分，经验方法
The STARFLAG handbook on collective animal behaviour: Part I, empirical methods
摘要：
动物集体行为的最令人吃惊的例子是由非常大的和有凝聚力的群体在三维空间中移动。典型的例子是鸟群、鱼群和昆虫群。然而，由于获得3D数据的技术难度，迄今为止进行的经验研究只考虑了几十只动物的松散群体。此外，这些研究很少在实地进行。最近，STARFLAG项目在野外条件下实现了数千只鸟类的3D重建，从而为新一代集体动物行为的定量研究开辟了道路。在这里，我们回顾了大型动物群体的3D数据采集的主要技术问题，并概述了STARFLAG项目所采用的一些方法解决方案。特别是，我们解释了如何解决立体对应-或匹配-问题，这是在过去的所有3D研究的主要瓶颈。
英文摘要：
The most startling examples of collective animal behaviour are provided by very large and cohesive groups moving in three dimensions. Paradigmatic examples are bird flocks, fish schools and insect swarms. However, because of the sheer technical difficulty of obtaining 3D data, empirical studies conducted to date have only considered loose groups of a few tens of animals. Moreover, these studies were very seldom conducted in the field. Recently the STARFLAG project achieved the 3D reconstruction of thousands of birds under field conditions, thus opening the way to a new generation of quantitative studies of collective animal behaviour. Here, we review the main technical problems in 3D data collection of large animal groups and we outline some of the methodological solutions adopted by the STARFLAG project. In particular, we explain how to solve the stereoscopic correspondence - or matching - problem, which was the major bottleneck of all 3D studies in the past.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
