Tracking individual honeybees among wildflower clusters with computer vision-facilitated pollinator monitoring.

ABSTRACT: Monitoring animals in their natural habitat is essential for advancement of animal behavioural studies, especially in pollination studies. Non-invasive techniques are preferred for these purposes as they reduce opportunities for research apparatus to interfere with behaviour. One potentially valuable approach is image-based tracking. However, the complexity of tracking unmarked wild animals using video is challenging in uncontrolled outdoor environments. Out-of-the-box algorithms currently present several problems in this context that can compromise accuracy, especially in cases of occlusion in a 3D environment. To address the issue, we present a novel hybrid detection and tracking algorithm to monitor unmarked insects outdoors. Our software can detect an insect, identify when a tracked in

SUBMITTER: Ratnayake MN 

PROVIDER: S-EPMC7877608 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature