Robust Statistics for Feature-based Active Appearance Models

Marcin Kopaczka, Philipp Gräbel, Dorit Merhof

2018

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.

Paper Citation

in Harvard Style

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 - Volume 1: ICETE, ISBN 978-989-758-319-3, pages 421-426. DOI: 10.5220/0006910004210426

in Bibtex Style

@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 - Volume 1: ICETE,},
year={2018},
pages={421-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006910004210426},
isbn={978-989-758-319-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on e-Business and Telecommunications - Volume 1: ICETE,
TI - Robust Statistics for Feature-based Active Appearance Models
SN - 978-989-758-319-3
AU - Kopaczka M.
AU - Gräbel P.
AU - Merhof D.
PY - 2018
SP - 421
EP - 426
DO - 10.5220/0006910004210426