A video frame conversion method, comprising: extracting a longest line segment of a 2D video frame; determining a first depth image of the 2D video frame according to a direction of the longest line segment; determining motion information of the 2D video frame according to a video frame adjacent to the 2D video frame; obtaining depth information of each pixel according to the motion information of each pixel; obtaining a second depth image of the 2D video frame according to the depth information of each pixel; and generating, according to the first depth image, the second depth image, and the 2D video frame, a 3D video frame corresponding to the 2D video frame; wherein the extracting a longest line segment of a 2D video frame comprises: performing smooth denoising on the 2D video frame by bilateral filtering; and detecting a bilaterally filtered 2D video frame by using a Hough transform technology, so as to extract the longest line segment of the 2D video frame; and wherein the determining a first depth image of the 2D video frame according to a direction of the longest line segment comprises: determining, according to the direction of the longest line segment, a depth transform direction of an initial depth template corresponding to the 2D video frame; dividing the bilaterally filtered 2D video frame into blocks wherein the blocks represent vertexes and absolute values of mean differences between the blocks represent edges, and clustering the blocks according to a predetermined threshold T wherein two vertexes belong to one cluster if the value of the edge between them is less than the threshold T; and obtaining the first depth image based on the initial depth template and according to the depth transform direction and the clustering of the blocks. extracting a longest line segment of a 2D video frame; determining a first depth image of the 2D video frame according to a direction of the longest line segment; determining motion information of the 2D video frame according to a video frame adjacent to the 2D video frame; obtaining depth information of each pixel according to the motion information of each pixel; obtaining a second depth image of the 2D video frame according to the depth information of each pixel; and generating, according to the first depth image, the second depth image, and the 2D video frame, a 3D video frame corresponding to the 2D video frame; performing smooth denoising on the 2D video frame by bilateral filtering; and detecting a bilaterally filtered 2D video frame by using a Hough transform technology, so as to extract the longest line segment of the 2D video frame; and determining, according to the direction of the longest line segment, a depth transform direction of an initial depth template corresponding to the 2D video frame; dividing the bilaterally filtered 2D video frame into blocks wherein the blocks represent vertexes and absolute values of mean differences between the blocks represent edges, and clustering the blocks according to a predetermined threshold T wherein two vertexes belong to one cluster if the value of the edge between them is less than the threshold T; and obtaining the first depth image based on the initial depth template and according to the depth transform direction and the clustering of the blocks.