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In order to realize real-time detection and recognition of multiple moving targets in aerial images of unmanned aerial vehicle (UAV), the stationary target and moving target were defined as background and foreground respectively, and the image stabilization technique was used to align each frame in the aerial image sequence with the adjacent frame, so as to overcome the influence of UAV flight movement on the image captured by camera rotation. The pedestrian and vehicle in the image are selected as the foreground, and the haar-like feature and cascade classifier are used to detect and recognize the targets in the image respectively. The dense optical flow is used to calculate the motion vectors of two continuous images, so as to distinguish the stationary target (background) and moving target (foreground), and the final image results only retain the region of the moving target. The proposed method was applied to the DroneVehicl aerial data set experiment, and the average frame per second reached 47.08 FPS, the detection accuracy was 94%, and showed high recall rate and F statistics, which could achieve real-time detection and recognition effect.