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ICCV
2011
IEEE

Object Segmentation in Video: A Hierarchical Variational Approach for Turning Point Trajectories into Dense Regions

12 years 3 months ago
Object Segmentation in Video: A Hierarchical Variational Approach for Turning Point Trajectories into Dense Regions
Point trajectories have emerged as a powerful means to obtain high quality and fully unsupervised segmentation of objects in video shots. They can exploit the long term motion difference between objects, but they tend to be sparse due to computational reasons and the difficulty in estimating motion in homogeneous areas. In this paper we introduce a variational method to obtain dense segmentations from such sparse trajectory clusters. Information is propagated with a hierarchical, nonlinear diffusion process that runs in the continuous domain but takes superpixels into account. We show that this process raises the density from 3% to 100% and even increases the average precision of labels.
Peter Ochs, Thomas Brox
Added 11 Dec 2011
Updated 11 Dec 2011
Type Journal
Year 2011
Where ICCV
Authors Peter Ochs, Thomas Brox
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