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Empirical mode decomposition-based facial pose estimation inside video sequences

Qing, C, Jiang, J and Yang, Z (2010) Empirical mode decomposition-based facial pose estimation inside video sequences Optical Engineering, 49 (3).

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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.

Item Type: Article
Authors :
NameEmailORCID
Qing, CUNSPECIFIEDUNSPECIFIED
Jiang, Jjianmin.jiang@surrey.ac.ukUNSPECIFIED
Yang, ZUNSPECIFIEDUNSPECIFIED
Date : 2010
Identification Number : https://doi.org/10.1117/1.3359510
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:25
Last Modified : 17 May 2017 15:03
URI: http://epubs.surrey.ac.uk/id/eprint/835291

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