Fast object segmentation in unconstrained video

We present a technique for separating foreground objects from the background in a video. Our method is fast, fully au-tomatic, and makes minimal assumptions about the video. This enables handling essentially unconstrained settings, including rapidly moving background, arbitrary object mo-tion and appearance, and non-rigid deformations and ar-ticulations. In experiments on two datasets containing over 1400 video shots, our method outperforms a state-of-the-art background subtraction technique [4] as well as meth-ods based on clustering point tracks [6, 18, 19]. Moreover, it performs comparably to recent video object segmentation methods based on object proposals [14, 16, 27], while being orders of magnitude faster. 1