Purpose -The purpose of this paper is to propose that the three-dimensional information of obstacles should be identified to allow unmanned aerial vehicles (UAVs) to detect and avoid obstacles existing in their flight path. Design/methodology/approach -First, the approximate outline of obstacles was detected using multi-scale-oriented patches (MOPS). At the same time, the spatial coordinates of feature points that exist in the internal outline of the obstacles were calculated through the scale-invariant feature transform (SIFT) algorithm. Finally, the results from MOPS and the results from the SIFT algorithm were merged to show the three-dimensional information of the obstacles. Findings -As the method proposed in this paper reconstructs only the approximate outline of obstacles, a quick calculation can be done. Moreover, as the outline information is combined through SIFT feature points, detailed three-dimensional information pertaining to the obstacles can be obtained. Practical implications -The proposed approach can be used efficiently in GPS-denied environments such as certain indoor environments. Originality/value -For the autonomous flight of small UAVs having a payload limit, this paper suggests a means of forming three-dimensional information about obstacles with images obtained from a monocular camera.