DYNAMIC WEIGHTING BASED ACTIVE CURVE PROPAGATION METHOD FOR VIDEO OBJECT SELECTION

Marwen Nouri, Emmanuel Marilly, Olivier Martinot, Nicole Vincent

2012

Abstract

Improving video user experience is an essential task allowing video based algorithms and systems to be more user-friendly. This paper addresses the problem of video object selection by introducing a new interactive framework based on the minimization of the Active Curve energy. Prior assumption and supervised learning can be used to segment images using both color and morphological information. To deal with the segmentation of arbitrary high level object, user interaction is needed to avoid the semantic gap. Hard constraints such scribbles can be drown by user on the first video frame, to roughly mark the object of interest, and there are then automatically propagated to designate the same object in the remainder of the sequence. The resulting scribbles can be used as hard constraints to achieve the whole segmentation process. The active curve model is adapted and new forces are included to govern the curves evolution frame by frame. A spatiotemporal optimization is used to ensure a coherent propagation. To avoid weight definition problem, as in classical active curve based algorithms, a new concept of dynamically adjusted weighting is introduced in order to improve the robustness of our curve propagation.

Paper Citation

in Harvard Style

Nouri M., Marilly E., Martinot O. and Vincent N. (2012). DYNAMIC WEIGHTING BASED ACTIVE CURVE PROPAGATION METHOD FOR VIDEO OBJECT SELECTION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-03-7, pages 5-11. DOI: 10.5220/0003818500050011

in Bibtex Style

@conference{visapp12,
author={Marwen Nouri and Emmanuel Marilly and Olivier Martinot and Nicole Vincent},
title={DYNAMIC WEIGHTING BASED ACTIVE CURVE PROPAGATION METHOD FOR VIDEO OBJECT SELECTION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={5-11},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003818500050011},
isbn={978-989-8565-03-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2012)
TI - DYNAMIC WEIGHTING BASED ACTIVE CURVE PROPAGATION METHOD FOR VIDEO OBJECT SELECTION
SN - 978-989-8565-03-7
AU - Nouri M.
AU - Marilly E.
AU - Martinot O.
AU - Vincent N.
PY - 2012
SP - 5
EP - 11
DO - 10.5220/0003818500050011