Guillermo Sapiro (University of Minnesota)
Wednesday, 30.12.2009, 10:30
We present Video SnapCut, a robust video object cutout system that significantly advances the state-of-the-art. In our system segmentation is achieved by the collaboration of a set of local classifiers, each adaptively integrating multiple local image features. We show how this segmentation paradigm naturally supports local user editing and propagates them across time. The object cutout system is completed with a novel coherent video matting technique. A comprehensive evaluation and comparison is presented, demonstrating the effectiveness of the proposed system at achieving high quality results, as well as the robustness of the system against various types of inputs. I will also show the system running as an Adobe After Effects plug-in.
Joint work with Xue Bail (Minnesota) and Jue Wang, David Simons, Daniel Wilk