Video Segmentation with Just a Few Strokes
IEEE International Conference on Computer Vision (ICCV), 2015
Abstract: As the use of videos is becoming more popular in computer vision,
the need for annotated video datasets increases. Such datasets are
required either as training data or simply as ground truth for
benchmark datasets. A particular challenge in video segmentation is
due to disocclusions, which hamper frame-to-frame propagation, in conjunction with non-moving objects. We show that a combination of motion from point trajectories, as known from motion
segmentation, along with minimal supervision can largely help solve
this problem.
Moreover, we integrate a new constraint that enforces consistency of
the color distribution in successive frames.
We quantify user interaction effort with respect to segmentation
quality on challenging ego motion videos. We compare our approach
to a diverse set of algorithms in terms of user effort and in terms of
performance on common video segmentation benchmarks.
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Link to data and code coming soon...
BibTex reference
@InProceedings{NSB15, author = "N.S. Nagaraja and F.R. Schmidt and T. Brox", title = "Video Segmentation with Just a Few Strokes", booktitle = "IEEE International Conference on Computer Vision (ICCV)", month = " ", year = "2015", url = "http://lmb.informatik.uni-freiburg.de/Publications/2015/NSB15" }