3D Face Pose Tracking using Low Quality Depth Cameras

Ahmed Rekik, Achraf Ben-Hamadou, Walid Mahdi

Abstract

This paper presents a new method for 3D face pose tracking in color image and depth data acquired by RGB-D (i.e., color and depth) cameras (e.g., Microsoft Kinect, Canesta, etc.). The method is based on a particle filter formalism and its main contribution lies in the combination of depth and image data to face the poor signal-to-noise ratio of low quality RGB-D cameras. Moreover, we consider a visibility constraint to handle partial occlusions of the face. We demonstrate the accuracy and the robustness of our method by performing a set of experiments on the Biwi Kinect head pose database.

References

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Paper Citation


in Harvard Style

Rekik A., Ben-Hamadou A. and Mahdi W. (2013). 3D Face Pose Tracking using Low Quality Depth Cameras . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 223-228. DOI: 10.5220/0004220202230228


in Bibtex Style

@conference{visapp13,
author={Ahmed Rekik and Achraf Ben-Hamadou and Walid Mahdi},
title={3D Face Pose Tracking using Low Quality Depth Cameras},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={223-228},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004220202230228},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - 3D Face Pose Tracking using Low Quality Depth Cameras
SN - 978-989-8565-48-8
AU - Rekik A.
AU - Ben-Hamadou A.
AU - Mahdi W.
PY - 2013
SP - 223
EP - 228
DO - 10.5220/0004220202230228