Pedestrian Detection in Unmanned Aerial Vehicle Scene

With the increasing adoption of unmanned aerial vehicles (UAVs), pedestrian detection with use of such vehicles has been attracting attention. Object detection algorithms based on deep learning have considerably progressed in recent years, but applying existing research results directly to the UAV perspective is difficult. Therefore, in this study, we present a new dataset called UAVs-Pedestrian, which contains various scenes and angles, for improving test results. To validate our dataset, we use the classical detection algorithms SSD, YOLO, and Faster-RCNN. Findings indicate that our dataset is challenging and conducive to the study of pedestrian detection using UAVs.