A PatchMatch-based Approachfor Matte Propagation in Videos

This thesis presents a temporally-coherent matte-propagation method for videos based on PatchMatch and edge-aware filtering. Given an input video and trimaps for a few frames, including the first and last, our approach generates alpha mattes for all frames of the video sequence. We also present a user scribble-based interface for video matting that takes advantage of the efficiency of our method to interactively refine the matte results. We perform quantitative comparisons against the state-of-the-art sparse-input video matting techniques and show that our method produces significantly better results according to three different metrics. We also perform qualitative comparisons against the state-of-the-art dense-input video matting techniques and show that ours produces similar quality results while requiring less than 7% of their user input.