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Authors: Marcin Kopaczka ; Philipp Gräbel and Dorit Merhof

Affiliation: Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen and Germany

Keyword(s): Active Appearance Models, Occlusion, Robust Cost Functions, Feature Descriptors.

Related Ontology Subjects/Areas/Topics: Digital Audio and Video Broadcasting ; Image and Video Processing, Compression and Segmentation ; Multimedia ; Multimedia and Communications ; Multimedia Signal Processing ; Telecommunications

Abstract: Active Appearance Models (AAM) are a well-established method for facial landmark detection and face tracking. Due to their widespread use, several additions to the original AAM algorithms have been proposed in recent years. Two previously proposed improvements that address different shortcomings are using robust statistics for occlusion handling and adding feature descriptors for improved landmark fitting performance. In this paper, we show that a combination of both methods is possible and provide a feasible and effective way to improve robustness and precision of the AAM fitting process. We describe how robust cost functions can be incorporated into the feature-based fitting procedure and evaluate our approach. We apply our method to the challenging 300-videos-in-the-wild dataset and show that our approach allows robust face tracking even under severe occlusions.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Kopaczka, M.; Gräbel, P. and Merhof, D. (2018). Robust Statistics for Feature-based Active Appearance Models. In Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - ICETE; ISBN 978-989-758-319-3; ISSN 2184-3236, SciTePress, pages 421-426. DOI: 10.5220/0006910005870592

@conference{icete18,
author={Marcin Kopaczka. and Philipp Gräbel. and Dorit Merhof.},
title={Robust Statistics for Feature-based Active Appearance Models},
booktitle={Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - ICETE},
year={2018},
pages={421-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006910005870592},
isbn={978-989-758-319-3},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - ICETE
TI - Robust Statistics for Feature-based Active Appearance Models
SN - 978-989-758-319-3
IS - 2184-3236
AU - Kopaczka, M.
AU - Gräbel, P.
AU - Merhof, D.
PY - 2018
SP - 421
EP - 426
DO - 10.5220/0006910005870592
PB - SciTePress