Qing, Chunmei and Jiang, Jianmin and Yang, Zhijing (2010) Empirical mode decomposition-based facial pose estimation inside video sequences. Optical Engineering, 49 (3). ISSN 0091-3286

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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
Additional Information:	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.
Keywords:	empirical mode decomposition, intrinsic mode function, mutual information, facial pose estimation, feature face, bandpass filter
Subjects:	G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:	College of Sciences > Faculty of Science > Lincoln School of Engineering
Depositing User:	Zhijing Yang
Date Deposited:	13 Feb 2011 19:46
Last Modified:	13 Mar 2013 08:55
URI:	http://eprints.lincoln.ac.uk/id/eprint/4018

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