1 March 2010 Empirical mode decomposition-based facial pose estimation inside video sequences
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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.
© (2010) Society of Photo-Optical Instrumentation Engineers (SPIE)
Ckhunmei Qing, Jianmin Jiang, Zhijing Yang, "Empirical mode decomposition-based facial pose estimation inside video sequences," Optical Engineering 49(3), 037401 (1 March 2010). https://doi.org/10.1117/1.3359510 . Submission:
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