Accelerometers and annotated video recordings of behaviours: a dataset for training behaviour classification models in goats
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2 juillet 2024
- doi: 10.57745/LGZBM1
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Knowledge, Classification ofCiter ce document
SARAH MAUNY et al., « Accelerometers and annotated video recordings of behaviours: a dataset for training behaviour classification models in goats », Recherche Data Gouv, ID : 10.57745/LGZBM1
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Eight dairy goats were equipped with accelerometers attached to the RFID ear tag of the animal. The accelerometers were programmed to record the acceleration on the x-y-z-axis at a frequency of 5 Hz for 24 consecutive hours. “Ruminating”, “head in the feeder”, “lying”, and “standing” behaviours were annotated from video recordings using the Observer XT software for 11 hours by a single trained observer using a pre-established ethogram. Raw acceleration data and associated behaviours (accessible online) are referred to as the input data for training the algorithm. The ACT4Behav (Accelerometer-based Classification tool for identifying Behaviours) pipeline was used to pre-process this raw data to train behaviour classification models (accessible online). Four models (accessible online) have been pre-trained for each of the four behaviours using the ACT4Behav pipeline.