大区域场景下基于无人机视角的目标计数方法

Target Counting Method Based on UAV View in Large Area Scenes

近年来,无人机因其灵活度高、机动性强在人群计数领域得到广泛应用。然而,现有的人群计数方法大多基于单视点,对于大范围、多摄像机场景下的多视点计数研究较少。为了解决这个问题,提出了一种基于无人机视角的目标计数方法以准确统计场景中的目标数量。选择临海区域进行数据采集,利用深度学习技术对采集的图像进行目标检测和图像拼接融合,在拼接后的图像中映射检测信息,并采用计数算法完成区域场景的计数任务。在公开数据集和该文制作的数据集上进行的实验验证了基于目标检测的计数算法的有效性。

In recent years,unmanned aerial vehicles(UAVs)have been widely used in thefield of crowd counting due to their highflexibility and maneuverability.However,most of the existing crowd counting methods are based on single viewpoints,with limited studies focusing on multi-viewpoint counting in large-scale,multi-camera scenes.To solve this problem,this paper proposes a UAV-based target counting method which can accurately count the number of targets in a given scene.Specifically,this study selects a sea-front area for data acquisition,utilizes deep learning technology for target detection and image stitching fusion on the acquired images.The detection information is then mapped onto the spliced image,and a counting algorithm is employed to fulfill the counting task for the regional scene.The effectiveness of the counting algorithm based on target detection is validated through experiments conducted on both public dataset and the dataset produced in this paper.