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Authors: Flavio de Barros Vidal ; Alexandre Zaghetto ; Diego A. L. Cordoba and Carla M. C. C. Koike

Affiliation: University of Brasilia, Brazil

Keyword(s): Visual Tracking, Particle Filter, Hybrid Resampling.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Robotics ; Software Engineering ; Tracking and Visual Navigation

Abstract: Occlusions and cluttered environments represent real challenges for visual tracking methods. In order to increase robustness for such situations, we present, in this article, a method for visual tracking using a Particle Filter with Hybrid Resampling. Our approach consists of using a particle filter to estimate the state of the tracked object, and both particles’ inertia and update information are used in the resampling stage. The proposed method is tested using a public benchmark and the results are compared with other tracking algorithms. The results show that our approach performs better in cluttered environments, as well as in situations with total or partial occlusions.

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Paper citation in several formats:
de Barros Vidal, F., Zaghetto, A., A. L. Cordoba, D. and M. C. C. Koike, C. (2014). Improving Visual Tracking Robustness in Cluttered and Occluded Environments using Particle Filter with Hybrid Resampling. In Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 3: VISAPP; ISBN 978-989-758-009-3; ISSN 2184-4321, SciTePress, pages 605-612. DOI: 10.5220/0004731006050612

@conference{visapp14,
author={Flavio {de Barros Vidal} and Alexandre Zaghetto and Diego {A. L. Cordoba} and Carla {M. C. C. Koike}},
title={Improving Visual Tracking Robustness in Cluttered and Occluded Environments using Particle Filter with Hybrid Resampling},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 3: VISAPP},
year={2014},
pages={605-612},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004731006050612},
isbn={978-989-758-009-3},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 3: VISAPP
TI - Improving Visual Tracking Robustness in Cluttered and Occluded Environments using Particle Filter with Hybrid Resampling
SN - 978-989-758-009-3
IS - 2184-4321
AU - de Barros Vidal, F.
AU - Zaghetto, A.
AU - A. L. Cordoba, D.
AU - M. C. C. Koike, C.
PY - 2014
SP - 605
EP - 612
DO - 10.5220/0004731006050612
PB - SciTePress