An occlusion robust image representation method is presented and applied to face recognition. In our method, Gabor phase difference representation is used mainly to resist occlusion. Based on the good ability of Gabor filters to capture image structure and the robustness to image occlusion shown here, Gabor phase features are expected to be discriminative and robust for face representation in occlusion case. Furthermore, we find that different scales and orientations of Gabor phase features lead to quite varied performance and then we analyze it carefully and find the effective Gabor phase (EGP) features. Moreover, we adopt spectral regression–based discriminant analysis, along with the extracted EGP features, to find the most discriminant subspace for classification. Thereby, an occlusion robust face image discriminant subspace is derived. Five kinds of feature representation methods and two subspace learning methods are compared for our recognition problem. Extensive experiments with various occlusion cases show the efficacy of the proposed method.
This paper presents a method for detecting corner points on 3D space curves. It is an extension of a previous work of distance accumulation for detecting corner points on 2D planar curves.6•7 A quantitative measure is proposed to define the "cornerness" of a 3D curve at a curve point, which has the advantage of being more stable and causing much less shape distortion than the traditional smoothing methods. In particular, this measure is invariant to scale, an attractive property for corner detection. Strategies are presented for reliable maximum selection. Experimental results with simulated data shows that the robustness and accuracy of the cornerness method.
Keywords - Corner detection, curvature, distance accumulation, maxima selection, curve representation, 3D curves.
Conference Committee Involvement (4)
Biometric Technology for Human Identification VII
5 April 2010 | Orlando, Florida, United States
Biometric Technology for Human Identification V
18 March 2008 | Orlando, Florida, United States
Biometric Technology for Human Identification IV
9 April 2007 | Orlando, Florida, United States
Biometric Technology for Human Identification III
17 April 2006 | Orlando (Kissimmee), Florida, United States
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