Unmanned aerial vehicle (UAV) based on visual positioning is prone to drift in a weak texture environment. To solve the problem, this study proposes a method integrating the improved Snake algorithm and ORB (oriented FAST and rotated BRIEF) feature optical flow to estimate the operating parameters of UAV. Firstly, Gaussian filtering is used to denoise the collected video frames. Then, the gray level co-occurrence matrix of video frames is calculated, and whether they are all in the weak texture area is judged. If they are all weak texture parts, ORB optical flow algorithm is used to estimate the parameters. If there is a non-weak texture area, the center of gravity of the area is calculated by the improved Snake model, by which the drift is estimated. With the homography matrix, the rotation component is obtained by decomposition. Laboratory experiments verify that the accuracy of parameter estimation is higher than 95% and the average processing time is as short as 0.025 s in both weak and non-weak texture areas.