Author:
Ipek Nusret,Van Damme Liesbeth G. W.,Tuyttens Frank A. M.,Verwaeren Jan
Abstract
AbstractIn recent years, computer vision has contributed significantly to the study of farm animal behavior. In complex environments such as commercial farms, however, the automated detection of social behavior and specific interactions between animals can be improved. The present study addresses the automated detection of agonistic interactions between caged animals in a complex environment, relying solely on computer vision. An automated pipeline including group-level temporal action segmentation, object detection, object tracking and rule-based action classification for the detection of agonistic interactions was developed and extensively validated at a level unique in the field. Comparing with observations made by human observers, our pipeline reaches 77% precision and 85% recall using a 5-min tolerance interval for the detection of agonistic interactions. Results obtained using this pipeline allow to construct time-dependent socio-matrices of a group of animals and derive metrics on the dominance hierarchy in a semi-automated manner. Group-housed breeding rabbits (does) with their litters in commercial farms are the main use-case in this work, but the idea is probably also applicable to other social farm animals.
Funder
Bijzonder Onderzoeksfonds UGent
Vlaamse regering
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献