LabelBee: a web platform for large-scale semi-automated analysis of honeybee behavior from video
LabelBee: a web platform for large-scale semi-automated analysis of honeybee behavior from video
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LabelBee:用于从视频中大规模半自动分析蜜蜂行为的网络平台
DOI:
10.1145/3359115.3359120
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发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Giray, Tugrul
中科院分区:
文献类型:
--
作者:
Mégret, Rémi;Rodriguez, Ivan F.;Ford, Isada Claudio;Acuña, Edgar;Agosto-Rivera, Jose L.;Giray, Tugrul
The LabelBee system is a web application designed to facilitate the collection, annotation and analysis of large amounts of honeybee behavior data from video monitoring. It is developed as part of NSF BIGDATA project "Large-scale multi-parameter analysis of honeybee behavior in their natural habitat", where we analyze continuous video of the entrance of bee colonies. Due to the large volume of data and its complexity, LabelBee provides advanced Artificial Intelligence and visualization capabilities to enable the construction of good quality datasets necessary for the discovery of complex behavior patterns. It integrates several levels of information: raw video, honeybee positions, decoded tags, individual trajectories and behavior events (entrance/exit, presence of pollen, fanning, etc.). This integration enables the combination of manual and automatic processing by the biologist end-users, who also share and correct their annotation through a centralized server. These annotations are used by the Computer Scientists to create new automatic models, and improve the quality of the automatic modules. The data constructed by this semi-automatized approach can then be exported for the analytic part, which is taking place on the same server using Jupyter notebooks for the extraction and exploration of behavior patterns.