NON-PARAMETRIC BAYESIAN ALIGNMENT AND RECOVERY OF OCCLUDED FACE USING DIRECT COMBINED MODEL

Ching-Ting Tu, Jenn-jier James Lien

Abstract

This paper focuses on the problem of recovering the occluded facial image automatically with the aid of domain specific prior knowledge and no manual face alignment or user-specified occlusion region is needed. The robust alignment and occlusion recovery are solved sequentially by a novel recovery scheme called the direct combined model (DCM). Local occluded facial patches are recovered by utilizing the information propagated from other non-occluded patches and is further constrained by a global facial geometry. The error residue between the recovered result and the geometric constraint is then used for updating the parameter of alignment function for the next iteration. Into this recovering framework, DCM efficiently and robustly updates the results of recovering and aligning based on a compact statistic model representing the prior updating knowledge. Our extensive experiment results demonstrate that the recovered images are quantitatively closer to the ground truth with no manual alignment and occlusion dection.

References

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Paper Citation


in Harvard Style

Tu C. and James Lien J. (2010). NON-PARAMETRIC BAYESIAN ALIGNMENT AND RECOVERY OF OCCLUDED FACE USING DIRECT COMBINED MODEL . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 495-498. DOI: 10.5220/0002833704950498


in Bibtex Style

@conference{visapp10,
author={Ching-Ting Tu and Jenn-jier James Lien},
title={NON-PARAMETRIC BAYESIAN ALIGNMENT AND RECOVERY OF OCCLUDED FACE USING DIRECT COMBINED MODEL},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={495-498},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002833704950498},
isbn={978-989-674-029-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - NON-PARAMETRIC BAYESIAN ALIGNMENT AND RECOVERY OF OCCLUDED FACE USING DIRECT COMBINED MODEL
SN - 978-989-674-029-0
AU - Tu C.
AU - James Lien J.
PY - 2010
SP - 495
EP - 498
DO - 10.5220/0002833704950498