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Recently,image local feature detection and description has been widely used in robot vision,It is decisive significance of a robust,rapid and high accuracy of visual feature detection and description algorithm for unmanned aerial vehicles real-time pose estimation and mapping. In view of the unmanned aerial vehicles RGB-D sensor Simultaneous Localization and Mapping(SLAM) characteristics,this paper discussed the performance of FAST,STAR,SIFT,SURF detection algorithm and the ORB,FREAK,SURF descriptor,and then compared different algorithm to find the most suitable feature detection method and the descriptor. Finally,the results of the experiment which is based on Eclipse and OpenCV platform,show that the FAST detection and FREAK descriptor is better than other methods suitable for unmanned aerial vehicles real-time visual SLAM.