Individual Animal and Herd Identification Using Custom YOLO v3 and v4 with Images Taken from a UAV Camera at Different Altitudes

In this study, an unmanned aerial vehicle (UAV) captures images of wild animals at different altitudes in order to compare the individual and herd identification capabilities of custom YOLO v3 and v4 models. Previous studies showed that UAVs can disturb animals in the wild at certain altitude, such that it is necessary to maintain altitude that does not disturb them. However, as the UAV altitude increases, the captured images lose features critical to YOLO in classification. We investigate and compare the accuracy of custom YOLO v3 and v4, especially from the acceptable minimum altitude and higher. We studied eight classes of wild African animals, namely, individual and herd of giraffes (Giraffa camelopardalis), individual and herd of white rhinos (Ceratotherium simum), individual and herd of wildebeests (Connochaetes taurinus), and individual and herd of zebras (Equus quagga). As UAV altitude increased, some image features are lost resulting to a model detection accuracy as low as 68.86%. The customised YOLO v4 model has 51.70 FPS outperforming customised YOLO v3 by an increased model speed of 13.7%.