School of Electrical and Electronic Engineering, University of Manchester, Manchester M13 9PL, UK.
J Insect Sci. 2021 Mar 1;21(2). doi: 10.1093/jisesa/ieab023.
We describe the development, field testing, and results from an automated 3D insect flight detection and tracking system for honey bees (Apis mellifera L.) (Hymenoptera: Apidae) that is capable of providing remarkable insights into airborne behavior. It comprises two orthogonally mounted video cameras with an observing volume of over 200 m3 and an offline analysis software system that outputs 3D space trajectories and inflight statistics of the target honey bees. The imaging devices require no human intervention once set up and are waterproof, providing high resolution and framerate videos. The software module uses several forms of modern image processing techniques with GPU-enabled acceleration to remove both stationary and moving artifact while preserving flight track information. The analysis system has thus far provided information not only on flight statistics (such as speeds and accelerations), but also on subtleties associated with flight behavior by generating heat maps of density and classifying flight patterns according to patrol and foraging behavior. Although the results presented here focus on behavior in the locale of a beehive, the system could be adapted to study a wide range of airborne insect activity.
我们描述了一种用于蜜蜂（Apis mellifera L.）（膜翅目：蜜蜂科）的自动 3D 昆虫飞行检测和跟踪系统的开发、现场测试和结果，该系统能够提供对空中行为的显著洞察。它由两个正交安装的摄像机组成，观察体积超过 200 立方米，还有一个离线分析软件系统，可输出目标蜜蜂的 3D 空间轨迹和飞行统计信息。成像设备一旦设置好，就不需要人工干预，而且防水，提供高分辨率和帧率的视频。软件模块使用多种形式的现代图像处理技术和 GPU 加速，在保留飞行轨迹信息的同时，去除静止和移动的伪影。该分析系统迄今为止不仅提供了飞行统计信息（例如速度和加速度），还通过生成密度热图并根据巡逻和觅食行为对飞行模式进行分类，提供了与飞行行为相关的细微信息。虽然这里介绍的结果主要集中在蜂巢环境中的行为，但该系统可以适应研究各种空中昆虫活动。
