The invention discloses an unmanned aerial vehicle man-machine interaction method based on three-dimensional continuous gesture recognition. The method comprises the following steps: acquiring human skeleton tracking data through a Kinect sensor, wherein the human skeleton tracking data at least include skeleton point tracking data of a right hand, a left hand, a right elbow, a left elbow, a right shoulder and a left shoulder; extracting a gesture track feature and preprocessing the gesture track feature, wherein preprocessing includes gesture start-stop detection, smooth filtering processing, resampling and position normalization; performing gesture recognition by using a neural network algorithm; and converting a gesture recognition result into a corresponding control instruction for controlling flight of an unmanned aerial vehicle. Through adoption of the method, gestures can be recognized accurately, so that a user can control flight of the unmanned aerial vehicle more freely and conveniently.