关键词: 无人机, 快速处理, SURF算法, Fast R-CNN网络, 新冠疫情

Abstract: During the epidemic period, it needs accurate field information and high-resolution orthophoto image as the basis for decision-making, but managers can not obtain information through intensive field inspection. The UAV field data acquisition speed is fast, the acquisition precision is high, the data quantity is all and so on superiority, but the traditional UAV orthophoto image processing speed cannot satisfy the project urgent need, therefore this article has made the omni-directional research from the UAV field field fast acquisition-the fast internal processing technology-the target achievement recognition, based on the improvement SURF UAV image fast processing algorithm, the method has the advantage of being fast. According to the advantages of fast and the key elements such as regular rectangle, prominent feature points and obvious contrast between light and shade in the image of the major engineering equipment, the orthophoto image can be quickly processed and fast can be used on this basis R-CNN network identifies on-site mechanical equipment to provide decision-making basis for the resumption of work. The corresponding results have been applied in the resumption of work of Xiong'an high-speed railway station during the period of COVID-19 epidemic.

Key words: UAV, rapid processing, SURF algorithm, Fast R-CNN network, COVID-19