Sparse Motion Segmentation using Propagation of Feature Labels

Pekka Sangi, Jari Hannuksela, Janne Heikkilä, Olli Silvén


The paper considers the problem of extracting background and foreground motions from image sequences based on the estimated displacements of a small set of image blocks. As a novelty, the uncertainty of local motion estimates is analyzed and exploited in the fitting of parametric object motion models which is done within a competitive framework. Prediction of patch labels is based on the temporal propagation of labeling information from seed points in spatial proximity. Estimates of local displacements are then used to predict the object motions which provide a starting point for iterative refinement. Experiments with both synthesized and real image sequences show the potential of the approach as a tool for tracking based online motion segmentation.


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Paper Citation

in Harvard Style

Sangi P., Hannuksela J., Heikkilä J. and Silvén O. (2013). Sparse Motion Segmentation using Propagation of Feature Labels . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 396-401. DOI: 10.5220/0004281203960401

in Bibtex Style

author={Pekka Sangi and Jari Hannuksela and Janne Heikkilä and Olli Silvén},
title={Sparse Motion Segmentation using Propagation of Feature Labels},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},

in EndNote Style

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Sparse Motion Segmentation using Propagation of Feature Labels
SN - 978-989-8565-48-8
AU - Sangi P.
AU - Hannuksela J.
AU - Heikkilä J.
AU - Silvén O.
PY - 2013
SP - 396
EP - 401
DO - 10.5220/0004281203960401