Focusing on the issue of ambient light interference affecting a depth camera and difficulty in obtaining the tree depth images, tree depth image generation algorithm based on small motion short video images is proposed. The algorithm tracks and matches the subpixel corners obtained after segmentation, uses the bundle adjustment to estimate the camera parameters. Intensive stereo matching and denoising of image sequences using plane scanning method to obtain tree depth images. The effectiveness of the proposed algorithm is verified using smartphones by collecting short video images of 1-2 s small movements, and the generated tree depth images exhibited a significant improvement in subjective effect. Verification on the depth image database NYU depth v2 revealed root mean square error is 60.58 and relative error is 0.34. Experiment results show that using this algorithm in a natural setting, a fine tree depth images can be effectively generated without the need for depth cameras, camera calibration, and training of a large number of RGB (Red, Green, Blue) images and depth images, which can reduce the data collection and storage costs. The research findings can provide a reference for the visual reconstruction of standing wood and measurement of the standing wood factor.