ENERGY-MINIMIZATION BASED MOTION ESTIMATION USING ADAPTIVE SMOOTHNESS PRIORS

Tarik Arici, Vural Aksakalli

2012

Abstract

Energy minimization algorithms are used in low-level computer vision applications for labeling tasks such as stereo-disparity estimation, image restoration, motion estimation, and optical flow. The energy function involves terms that evaluate the goodness of a solution in terms of a prior knowledge in addition to data terms. The most widely used priors are smoothness-based priors, which enhance the quality significantly. However, the smoothness assumption is not valid across discontinuities (e.g. motion boundaries). We present a method to update the weights of smoothness terms using the dual problem when the approximation algorithm is iterative. The dual of the primal energy minimization problem is used to infer about the validity of the smoothness prior and impose it more correctly at each iteration. We demonstrate the effectiveness of this method against the state-of-the-art in the optical flow literature.

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Paper Citation


in Harvard Style

Arici T. and Aksakalli V. (2012). ENERGY-MINIMIZATION BASED MOTION ESTIMATION USING ADAPTIVE SMOOTHNESS PRIORS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 201-207. DOI: 10.5220/0003805202010207


in Harvard Style

Arici T. and Aksakalli V. (2012). ENERGY-MINIMIZATION BASED MOTION ESTIMATION USING ADAPTIVE SMOOTHNESS PRIORS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 201-207. DOI: 10.5220/0003805202010207


in Bibtex Style

@conference{visapp12,
author={Tarik Arici and Vural Aksakalli},
title={ENERGY-MINIMIZATION BASED MOTION ESTIMATION USING ADAPTIVE SMOOTHNESS PRIORS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={201-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003805202010207},
isbn={978-989-8565-04-4},
}


in Bibtex Style

@conference{visapp12,
author={Tarik Arici and Vural Aksakalli},
title={ENERGY-MINIMIZATION BASED MOTION ESTIMATION USING ADAPTIVE SMOOTHNESS PRIORS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={201-207},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003805202010207},
isbn={978-989-8565-04-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - ENERGY-MINIMIZATION BASED MOTION ESTIMATION USING ADAPTIVE SMOOTHNESS PRIORS
SN - 978-989-8565-04-4
AU - Arici T.
AU - Aksakalli V.
PY - 2012
SP - 201
EP - 207
DO - 10.5220/0003805202010207


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - ENERGY-MINIMIZATION BASED MOTION ESTIMATION USING ADAPTIVE SMOOTHNESS PRIORS
SN - 978-989-8565-04-4
AU - Arici T.
AU - Aksakalli V.
PY - 2012
SP - 201
EP - 207
DO - 10.5220/0003805202010207