Dirichlet-tree Distribution Enhanced Random Forests for Head Pose Estimation

Yuanyuan Liu, Jingying Chen, Leyuan Liu, Yujiao Gong, Nan Luo

2014

Abstract

Head pose estimation is important in human-machine interfaces. However, illumination variation, occlusion and low image resolution make the estimation task difficult. Hence, a Dirichlet-tree distribution enhanced Random Forests approach (D-RF) is proposed in this paper to estimate head pose efficiently and robustly under various conditions. First, Gabor features of the facial positive patches are extracted to eliminate the influence of occlusion and noise. Then, the D-RF is proposed to estimate the head pose in a coarse-to-fine way. In order to improve the discrimination capability of the approach, an adaptive Gaussian mixture model is introduced in the tree distribution. The proposed method has been evaluated with different data sets spanning from -90º to 90º in vertical and horizontal directions under various conditions.The experimental results demonstrate the approach’s robustness and efficiency.

Paper Citation

in Harvard Style

Liu Y., Chen J., Liu L., Gong Y. and Luo N. (2014). Dirichlet-tree Distribution Enhanced Random Forests for Head Pose Estimation . In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-018-5, pages 87-95. DOI: 10.5220/0004825000870095

in Bibtex Style

@conference{icpram14,
author={Yuanyuan Liu and Jingying Chen and Leyuan Liu and Yujiao Gong and Nan Luo},
title={Dirichlet-tree Distribution Enhanced Random Forests for Head Pose Estimation},
booktitle={Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2014},
pages={87-95},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004825000870095},
isbn={978-989-758-018-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Dirichlet-tree Distribution Enhanced Random Forests for Head Pose Estimation
SN - 978-989-758-018-5
AU - Liu Y.
AU - Chen J.
AU - Liu L.
AU - Gong Y.
AU - Luo N.
PY - 2014
SP - 87
EP - 95
DO - 10.5220/0004825000870095