MBT3D: Deep learning based multi-object tracker for bumblebee 3D flight path estimation.

ABSTRACT: This work presents the Multi-Bees-Tracker (MBT3D) algorithm, a Python framework implementing a deep association tracker for Tracking-By-Detection, to address the challenging task of tracking flight paths of bumblebees in a social group. While tracking algorithms for bumblebees exist, they often come with intensive restrictions, such as the need for sufficient lighting, high contrast between the animal and background, absence of occlusion, significant user input, etc. Tracking flight paths of bumblebees in a social group is challenging. They suddenly adjust movements and change their appearance during different wing beat states while exhibiting significant similarities in their individual appearance. The MBT3D tracker, developed in this research, is an adaptation of an existing ant tracking

SUBMITTER: Stiemer LN 

PROVIDER: S-EPMC10516433 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature