A New Dataset for Video-based Cow Behavior Recognition

Abstract

A new video based multi behavior dataset for cows, CBVD-5, is introduced in this paper.The dataset consists of ranch monitoring footage collected by 7 cameras, including 687 video segment samples and 206100 image samples, covering five daily behaviors of cows. These behaviors were selected because of the need for ranch farming. The video collection is completed by a fixed camera installed by oneself, ensuring that the monitoring coverage of the ranch is not affected by blind spots.The annotation coordinates and category labels of each individual cow in the image, as well as the generated configuration file, are also saved in the dataset. With this dataset,we propose a slowfast cow multi behavior recognition model based on video sequences as the baseline evaluation model.The experimental results show that the model can effectively learn corresponding category labels from the behavior type data of the dataset, with an error rate of 21.28\% on the test set. The dataset will be made freely available to researchers world-wide. In addition to cow behavior recognition, the dataset can also be used for cow target detection, and so on.