Video Dataset of Sheep Activity (Grazing, Running, Sitting)

Published: 24 October 2023| Version 1 | DOI: 10.17632/h5ppwx6fn4.1
Contributors:
Bilal Khan, Nathan Kelly

Description

A primary dataset capturing five distinct types of sheep activities in realistic settings has been constructed at various resolutions and viewing angles, targeting the expansion of the domain knowledge for non-contact virtual fencing approaches. The present dataset can be used to develop non-invasive approaches for sheep activity detection, which can be proven useful for farming activities including, but not limited to: (i) sheep counting, (ii) virtual fencing, (iii) behavior detection for health status, and (v) effective sheep breeding. Sheep activity classes include grazing, running, sitting, standing, and walking. The activities of individuals, as well as herds of sheep, were recorded at different resolutions and angles to provide a dataset of diverse characteristics. Overall, a total of 149,327 frames from 417 videos (the equivalent of 59 minutes of footage) are presented with a balanced set for each activity class, which can be utilized for robust non-invasive detection models based on computer vision techniques. Despite a decent existence of noise within the original data (e.g., segments with no sheep present, multiple sheep in single frames, multiple activities by one or more sheep in single as well as multiple frames, segments with sheep alongside other non-sheep objects), we provide original videos and the extracted frames (with videos and frames containing humans omitted for privacy reasons). The present dataset includes diverse sheep activity characteristics and can be useful for robust detection and recognition models, as well as advanced activity detection models as a function of time for the applications. Note: We separated three additional classes of the same dataset into a separate Mendeley dataset since the size of the video set was above the allowed limit by Mendeley Data Repository. Those three additional classes are uploaded in a separate dataset which can be accessed via (Reference below with DOI: 10.17632/w65pvb84dg.1). Three classes from the DOI (provided below) can be copied into this main folder in order to have the complete dataset with 5 distinct classes. Khan, Bilal; Kelly, Nathan (2023), “Video Dataset of Sheep Activity (Standing and Walking)”, Mendeley Data, V1, doi: 10.17632/w65pvb84dg.1

Files

Steps to reproduce

This dataset contains three classes (Grazing, Running, Sitting) in three folders where the corresponding videos are stored. Only unzipping/extracting the zipped folder is required for this dataset. We separated three additional classes (Standing, Walking, Miscellaneous) of the same video set into a separate Mendeley dataset since the size of the video set was above the allowed limit by Mendeley Data Repository. Those three additional classes are uploaded in a separate dataset which can be accessed via (Reference below with DOI: 10.17632/w65pvb84dg.1). Three classes from the DOI (provided below) can be copied into this main folder in order to have the complete dataset with 5 distinct classes. Khan, Bilal; Kelly, Nathan (2023), “Video Dataset of Sheep Activity (Standing and Walking)”, Mendeley Data, V1, doi: 10.17632/w65pvb84dg.1

Institutions

California State University San Bernardino

Categories

Computer Vision, Sheep Behavior, Pattern Recognition, Surveillance, Deep Learning, Virtual Screening

Licence