Machine Learning for Video-Based Rendering

This work extends the new paradigm for computer animation, video textures, whichuses recorded video to generate novel animations by replaying the video samples in a new order. Here we concentrate on video sprites, which are a special type of video texture. We present methods to create suchanimations by finding a sequence of sprite samples that is both visually smooth and follows a desired path. To estimate visual smoothness, we train a linear classifier to estimate visual similarity between video samples. If the motion path is known in advance, we use beam search to find a good sample sequence.