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2008
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Significant jet point for facial image representation and recognition

9 years 4 months ago
Significant jet point for facial image representation and recognition
Gabor wavelet related feature extraction and classification is an important topic in image analysis and pattern recognition. Gabor features can be used either holistically or analytically. While holistic approaches involve significant computational complexity, existing analytic approaches require explicit correspondence of predefined feature points for classification. Different from these approaches, this paper presents a new analytic Gabor method for face recognition. The proposed method attaches Gabor features on a set of shape-driven sparse points to describe both geometric and textural information. Neither the number nor the correspondence of these points is needed. A variant of Hausdorff distance is employed to recognize faces. The experiments performed on AR database demonstrated that the proposed algorithm is effective to identify individuals in various circumstances, such as under expression and illumination changes.
Sanqiang Zhao, Yongsheng Gao
Added 20 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2008
Where ICIP
Authors Sanqiang Zhao, Yongsheng Gao
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