Annotated Behaviour and Observability Dataset (ABODe)
收藏DataCite Commons2023-04-27 更新2025-04-17 收录
下载链接：
https://datashare.ed.ac.uk/handle/10283/4837
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资源简介：
This DataShare dataset pertains to behaviour classification for group-housed mice as documented in the Thesis "Automated Identification and Behaviour Classification for Modelling Social Dynamics in Group-Housed Mice" (2023) by Michael Camilleri. It grew out of a collaboration with the Mary Lyon Centre at MRC Harwell, with the need to automatically classify the behaviours of group-housed mice using only video recordings in the home-cage. The challenges include the multiple mice which must be tracked/identified and the level of occlusion. We provide herein an annotated dataset containing mouse videos, identities (by bounding boxes and ground-plate positions) and annotator labelling (by an expert animal care technician) of the individual behaviours. The dataset can be used to train and evaluate spatio-temporal activity localisation methods that classify the behaviour of each mouse at 1s intervals on extended videos. Further details are available at https://github.com/michael-camilleri/ABODe.
提供机构：
University of Edinburgh. School of Informatics. Institute of Adaptive and Neural Computation
创建时间：
2023-03-30
