Ben-Dov Omri, Beatus Tsevi
The Institute of Life Science, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
Insects. 2022 Nov 3;13(11):1018. doi: 10.3390/insects13111018.
Insect flight is a complex interdisciplinary phenomenon. Understanding its multiple aspects, such as flight control, sensory integration, physiology and genetics, often requires the analysis of large amounts of free flight kinematic data. Yet, one of the main bottlenecks in this field is automatically and accurately extracting such data from multi-view videos. Here, we present a model-based method for the pose estimation of free-flying fruit flies from multi-view high-speed videos. To obtain a faithful representation of the fly with minimum free parameters, our method uses a 3D model that includes two new aspects of wing deformation: A non-fixed wing hinge and a twisting wing surface. The method is demonstrated for free and perturbed flight. Our method does not use prior assumptions on the kinematics apart from the continuity of the wing pitch angle. Hence, this method can be readily adjusted for other insect species.
昆虫飞行是一个复杂的跨学科现象。要理解其多个方面,如飞行控制、感官整合、生理学和遗传学,通常需要分析大量自由飞行的运动学数据。然而,该领域的主要瓶颈之一是如何从多视角视频中自动且准确地提取此类数据。在此,我们提出一种基于模型的方法,用于从多视角高速视频中估计自由飞行果蝇的姿态。为了用最少的自由参数获得果蝇的真实表示,我们的方法使用了一个三维模型,该模型包含机翼变形的两个新方面:一个非固定的机翼铰链和一个扭曲的机翼表面。该方法在自由飞行和受扰飞行中均得到了验证。除了机翼俯仰角的连续性之外,我们的方法不使用关于运动学的先验假设。因此,该方法可以很容易地针对其他昆虫物种进行调整。