ENHANCING MEMORY-BASED PARTICLE FILTER WITH DETECTION-BASED MEMORY ACQUISITION FOR ROBUSTNESS UNDER SEVERE OCCLUSION

Dan Mikami, Kazuhiro Otsuka, Shiro Kumano, Junji Yamato

Abstract

A novel enhancement for the memory-based particle filter is proposed for visual pose tracking under severe occlusions. The enhancement is the addition of a detection-based memory acquisition mechanism. The memorybased particle filter, M-PF, is a particle filter that predicts prior distributions from past history of target state, which achieved high robustness against complex dynamics of a tracking target. Such high performance requires sufficient history stored in memory. Conventionally, M-PF conducts online memory acquisition which assumes simple target’s dynamics without occlusions for guaranteeing high quality histories. The requirement of memory acquisition narrows the coverage of M-PF in practice. In this paper, we propose a new memory acquisition mechanism for M-PF. The key idea is to use a target detector that can produce additional prior distribution of the target state. We call it M-PFDMA for M-PF with detection-based memory acquisition. The detection-based prior distribution well predicts possible target position/pose even in limited visibility conditions caused by occlusions. Such better prior distributions contribute to stable estimation of target state, which is then added to memorized data. As a result, M-PFDMA can start with no memory entries but soon achieve stable tracking even under severe occlusions. Experiments confirm M-PFDMA’s good performance in such conditions.

References

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Paper Citation


in Harvard Style

Mikami D., Otsuka K., Kumano S. and Yamato J. (2012). ENHANCING MEMORY-BASED PARTICLE FILTER WITH DETECTION-BASED MEMORY ACQUISITION FOR ROBUSTNESS UNDER SEVERE OCCLUSION . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 208-215. DOI: 10.5220/0003808302080215


in Bibtex Style

@conference{visapp12,
author={Dan Mikami and Kazuhiro Otsuka and Shiro Kumano and Junji Yamato},
title={ENHANCING MEMORY-BASED PARTICLE FILTER WITH DETECTION-BASED MEMORY ACQUISITION FOR ROBUSTNESS UNDER SEVERE OCCLUSION},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={208-215},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003808302080215},
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 - ENHANCING MEMORY-BASED PARTICLE FILTER WITH DETECTION-BASED MEMORY ACQUISITION FOR ROBUSTNESS UNDER SEVERE OCCLUSION
SN - 978-989-8565-04-4
AU - Mikami D.
AU - Otsuka K.
AU - Kumano S.
AU - Yamato J.
PY - 2012
SP - 208
EP - 215
DO - 10.5220/0003808302080215