Fast object segmentation in unconstrained video

被引:373
作者
Papazoglou, Anestis [1 ]
Ferrari, Vittorio [1 ]
机构
[1] Univ Edinburgh, Edinburgh EH8 9YL, Midlothian, Scotland
来源
2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) | 2013年
关键词
D O I
10.1109/ICCV.2013.223
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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-the-art 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.
引用
收藏
页码:1777 / 1784
页数:8
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