Abstract: The design of video fusion transform model is an important step in video fusion. Projection transformation matrix is used in the current multiple cameras video fusion transform model, but it usually causes the severe distortion. When there are larger parallax among cameras, the distortion will be larger. So the traditional video fusion transform model has a higher request for the camera position. For this problem, this paper presents a shape and content preserving video fusion transformation model. Finding the seam and getting the similarity transformation matrix are the key of the proposed model. The algorithm of dynamic programming is used to find the seam, and the similarity transformation matrix is calculated according to the continuity between the projection transformation and the similarity transformation. When we get the seam, the space is divided into two half spaces. Projection transformation model is used in the left space, and similarity transformation model is used in the right space. The combination of projection transformation and similarity transformation protects the shape does not occur with larger tensile scaling. In addition, content preserving algorithm is used in the seam neighborhood, which caused a better result. Applying this new model to the actual video data, the experimental results show that this method has high robustness and practicality