Uncertainty Fusion based Object Recognition and Tracking in Maritime Scenes using Spatiotemporal Active Contours

Ikhlef Bechar, Frederic Bouchara, Thibault Lelore, Vincente Guis, Michel Grimaldi

2014

Abstract

This article addresses the problem of near real time video analysis of a maritime scene using a (moving) airborne RGB video camera in the goal of detecting and eventually recognizing a target maritime vessel. This is a very challenging problem mainly due to the high level of uncertainty of a maritime scene including a dynamic and noisy background, camera’s and target’s motions, and broad variability of background’s versus target’s appearances. We propose an approach which attempts to combine several types of spatiotemporal uncertainty in a single probabilistic framework. This allows to achieve a likelihood ratio with respect to any possible spatiotemporal configuration of the 2D+T video volume. Using the MAP estimation criterion, such a problem can be recast as as an energy minimization problem that we solve efficiently using a spatiotemporal active contour approach. We demonstrate the feasibility of the proposed approach using real maritime videos.

Paper Citation

in Harvard Style

Bechar I., Bouchara F., Lelore T., Guis V. and Grimaldi M. (2014). Uncertainty Fusion based Object Recognition and Tracking in Maritime Scenes using Spatiotemporal Active Contours . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 682-689. DOI: 10.5220/0004755406820689

in Bibtex Style

@conference{visapp14,
author={Ikhlef Bechar and Frederic Bouchara and Thibault Lelore and Vincente Guis and Michel Grimaldi},
title={Uncertainty Fusion based Object Recognition and Tracking in Maritime Scenes using Spatiotemporal Active Contours},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={682-689},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004755406820689},
isbn={978-989-758-003-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Uncertainty Fusion based Object Recognition and Tracking in Maritime Scenes using Spatiotemporal Active Contours
SN - 978-989-758-003-1
AU - Bechar I.
AU - Bouchara F.
AU - Lelore T.
AU - Guis V.
AU - Grimaldi M.
PY - 2014
SP - 682
EP - 689
DO - 10.5220/0004755406820689