Fast Object Segmentation in Unconstrained Video
Abstract
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 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.
Cite
Text
Papazoglou and Ferrari. "Fast Object Segmentation in Unconstrained Video." International Conference on Computer Vision, 2013. doi:10.1109/ICCV.2013.223Markdown
[Papazoglou and Ferrari. "Fast Object Segmentation in Unconstrained Video." International Conference on Computer Vision, 2013.](https://mlanthology.org/iccv/2013/papazoglou2013iccv-fast/) doi:10.1109/ICCV.2013.223BibTeX
@inproceedings{papazoglou2013iccv-fast,
title = {{Fast Object Segmentation in Unconstrained Video}},
author = {Papazoglou, Anestis and Ferrari, Vittorio},
booktitle = {International Conference on Computer Vision},
year = {2013},
doi = {10.1109/ICCV.2013.223},
url = {https://mlanthology.org/iccv/2013/papazoglou2013iccv-fast/}
}