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Advances in Moving Face Recognition
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Author(s): Hui Fang (Swansea University, UK), Nicolas Costen (Manchester Metropolitan University, UK), Phil Grant (Swansea University, UK)and Min Chen (Swansea University, UK)
Copyright: 2011
Pages: 12
Source title:
Applied Signal and Image Processing: Multidisciplinary Advancements
Source Author(s)/Editor(s): Rami Qahwaji (University of Bradford, UK), Roger Green (University of Warwick, UK)and Evor L. Hines (University of Warwick, UK)
DOI: 10.4018/978-1-60960-477-6.ch010
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Abstract
This chapter describes the approaches to extracting features via the motion subspace for improving face recognition from moving face sequences. Although the identity subspace analysis has achieved reasonable recognition performance in static face images, more recently there has been an interest in motion-based face recognition. This chapter reviews several state-of-the-art techniques to exploit the motion information for recognition and investigates the permuted distinctive motion similarity in the motion subspace. The motion features extracted from the motion subspaces are used to test the performance based on a verification experimental framework. Through experimental tests, the results show that the correlations between motion eigen-patterns significantly improve the performance of recognition.
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