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Authors: Oliver Mothes and Joachim Denzler

Affiliation: Friedrich Schiller University Jena, Germany

ISBN: 978-989-758-227-1

Keyword(s): Landmark Tracking, Active Appearance Models, Whitened Histograms of Orientations.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Medical Image Applications ; Motion, Tracking and Stereo Vision ; Optical Flow and Motion Analyses

Abstract: For animal bipedal locomotion analysis, an immense amount of recorded image data has to be evaluated by biological experts. During this time-consuming evaluation single anatomical landmarks have to be annotated in each image. In this paper we reduce this effort by automating the annotation with a minimum level of user interaction. Recent approaches, based on Active Appearance Models, are improved by priors based on anatomical knowledge and an online tracking method, requiring only a single labeled frame. However, the limited search space of the online tracker can lead to a template drift in case of severe self-occlusions. In contrast, we propose a one-shot learned tracking-by-detection prior which overcomes the shortcomings of template drifts without increasing the number of training data. We evaluate our approach based on a variety of real-world X-ray locomotion datasets and show that our method outperforms recent state-of-the-art concepts for the task at hand.

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Paper citation in several formats:
Mothes, O. and Denzler, J. (2017). Anatomical Landmark Tracking by One-shot Learned Priors for Augmented Active Appearance Models.In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6 VISAPP: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 246-254. DOI: 10.5220/0006133302460254

@conference{visapp17,
author={Oliver Mothes. and Joachim Denzler.},
title={Anatomical Landmark Tracking by One-shot Learned Priors for Augmented Active Appearance Models},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6 VISAPP: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={246-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006133302460254},
isbn={978-989-758-227-1},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6 VISAPP: VISAPP, (VISIGRAPP 2017)
TI - Anatomical Landmark Tracking by One-shot Learned Priors for Augmented Active Appearance Models
SN - 978-989-758-227-1
AU - Mothes, O.
AU - Denzler, J.
PY - 2017
SP - 246
EP - 254
DO - 10.5220/0006133302460254

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