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Optical Engineering

Empirical mode decomposition-based facial pose estimation inside video sequences
Author(s): Ckhunmei Qing; Jianmin Jiang; Zhijing Yang
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Paper Abstract

We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is exploited to decompose input facial images into a number of intrinsic mode function (IMF) components, which redistribute the effect of noise, expression changes, and illumination variations as such that, when the input facial image is described by the selected IMF components, all the negative effects can be minimized. Extensive experiments were carried out in comparisons to existing representative techniques, and the results show that the proposed algorithm achieves better pose-estimation performances with robustness to noise corruption, illumination variation, and facial expressions.

Paper Details

Date Published: 1 March 2010
PDF: 10 pages
Opt. Eng. 49(3) 037401 doi: 10.1117/1.3359510
Published in: Optical Engineering Volume 49, Issue 3
Show Author Affiliations
Ckhunmei Qing, Univ. of Bradford (United Kingdom)
Jianmin Jiang, Univ. of Bradford (United Kingdom)
Zhijing Yang, Sun Yat-Sen Univ. (China)


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