Research on goat herd tracking in natural scenes based on improved DeepSORT

Ranch management gradually tends to be intelligent with the development of the times, and in the process of realizing intelligence, livestock tracking technology appears to be crucial. In order to realize the fast tracking of sheep, a sheep tracking method based on the improved DeepSORT algorithm is designed. Firstly, the process of the tracking algorithm is improved by adding one round of IOU matching and lowering the threshold of the added IOU matching; when performing the trajectory matching, the spatial and positional similarities and correlations are taken into account at the same time, which helps to improve the accuracy and robustness of the target matching; and the state vectors of the Kalman filtering are improved to improve the robustness of the target tracking. Experiments are conducted on the dataset, and the tracking accuracy of the improved DeepSORT algorithm is 94.6%, which is 5.3%, 7.55%, 4.35%, and 2.2% higher than the tracking accuracies of ByteTrack, JDE, SORT, and DeepSORT algorithms, respectively, and it has a very good generalization ability. The algorithm can track sheep accurately and quickly, which provides new technical support for animal welfare.