Fast Object Segmentation in Unconstrained Video

Anestis Papazoglou, Vittorio Ferrari
2013 2013 IEEE International Conference on Computer Vision  
We present a technique for separating foreground objects from the background in a video. Our method is fast, fully automatic, and makes minimal assumptions about the video. This enables handling essentially unconstrained settings, including rapidly moving background, arbitrary object motion and appearance, and non-rigid deformations and articulations. In experiments on two datasets containing over 1400 video shots, our method outperforms a state-of-theart background subtraction technique [4] as
more » ... on technique [4] as well as methods 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.
doi:10.1109/iccv.2013.223 dblp:conf/iccv/PapazoglouF13 fatcat:oi2tmxdxffghxpfopduxzwyrpu