  Autonomous and safe landing is important for unmanned aerial vehicles. We
present a monocular and stereo image based method for fast and accurate landing
zone evaluation for UAVs in various scenarios. Many existing methods rely on
Lidar or depth sensor to provide accurate and dense surface reconstruction. We
utilize stereo images to evaluate the slope and monocular images to compute
homography error. By combining them together, our approach works for both rigid
and non-rigid dynamic surfaces. Experiments on many outdoor scenes such as
water, grass and roofs, demonstrate the robustness and effectiveness of our
approach.
