Machine Vision-based Trajectory Tracking of Honey Bee Crawling Motion

Abstract

With the maturity of machine vision technology in artificial intelligence and the rise of the concept of "smart agriculture", machine vision-based methods are widely interested in studying biological behavior, but the technology for acquiring biological behavior information is still unsound. In this paper, we propose a machine vision-based bee crawling trajectory tracking method, which automatically records the bee crawling trajectory in the video information and obtains the description of bee crawling behavior. The method establishes the description of bee crawling motion through bee target detection, bee crawling motion tracking and bee crawling motion prediction as a method to study bee crawling behavior through artificial intelligence techniques. The method has the advantages of high timeliness and low labor cost, and reduces the problems of traditional research through manual observation records and bioassays methods with high influence of human subjective judgment factors and high application costs.