Stereoscopic Image Enabled Animation Art Design Exploration

With the emergence of movie art, many related art forms were born. Animation art has gained a large number of audiences due to its exaggerated expression. In order to improve the problems of character image overlapping and scene distortion that may occur in the original two-dimensional space, this paper constructs a semi-global stereo image matching algorithm based on the use of point cloud matching in the animation screen for the determination of the screen position and the morphology of the animated character. To compensate for the radiation difference in the stereo image matching algorithm, object-square geometric constraints are proposed to improve the matching cost calculation process. After calculating the matching cost, the original animation model is optimized or rebuilt by creating a depth space image. Taking Disney animation characters as an example, the number of joints required for the reconstruction of the “Snow White” character is 2.9 times more than that of the “Mickey” character, but the reconstruction time of the skeleton is only 12 times longer than that of the “Mickey” character. However, the skeleton reconstruction time is only 12.1 seconds longer than that of the “Mickey” character, which indicates that the algorithm proposed in this paper does not produce a large difference in reconstruction time due to the difference in characters. For the construction of animated indoor scenes, in the eight experimental scenes, the maximum number of grids can be divided into 42365412, and the processing time required is 276.413 seconds. It shows that the algorithm in this paper is capable of subregionally refining the indoor space of the animation. The proposed semi-global stereo image matching-based pan can quickly reconstruct animated character models and animated scenes, as can be seen.