Interactive Video Cutout
Jue Wang, Pravin Bhat, Alex Colburn, Maneesh Agrawala, Michael Cohen
Abstract
We present an interactive system for efficiently extracting foreground objects from a video. We extend previous min-cut based image segmentation techniques to the domain of video with four new contributions. We provide a novel painting-based user interface that allows users to easily indicate the foreground object across space and time. We introduce a hierarchical mean-shift preprocess in order to minimize the number of nodes that min-cut must operate on. Within the min-cut we also define new local cost functions to augment the global costs defined in earlier work. Finally, we extend 2D alpha matting methods designed for images to work with 3D video volumes. We demonstrate that our matting approach preserves smoothness across both space and time. Our interactive video cutout system allows users to quickly extract foreground objects from video sequences for use in a variety of applications including compositing onto new backgrounds and NPR cartoon style rendering.
Our interactive video cutout system makes it easy to extract the foreground objects in these videos of an elephant and a skatebaorder. We then composite these objects onto a third background video to form a new video in which the skateboarder skates on the elephant.