Gabor filters are biologically motivated convolution kernels that have been widely used in the fi... more Gabor filters are biologically motivated convolution kernels that have been widely used in the field of computer vision and, specially, in face recognition during the last decade. This paper proposes a statistical model of Gabor coefficients extracted from face images using generalized Gaussian distributions (GGD's). By measuring the Kullback-Leibler distance (KLD) between the pdf of the GGD and the relative frequency of the coefficients, we conclude that GGD's provide an accurate modeling. The underlying statistics allow us to reduce the required amount of data to be stored (i.e. data compression) via Lloyd-Max quantization. Verification experiments on the XM2VTS database show that performance does not drop when, instead of the original data, we use quantized coefficients.
Let (ΛV,d) be the Sullivan model of a pure elliptic space S. We give an algorithm, based on the c... more Let (ΛV,d) be the Sullivan model of a pure elliptic space S. We give an algorithm, based on the computation of the Hilbert function of certain ideal, that provides a lower and an upper bound for the rational L.–S. category of S,cat0(ΛV,d). When S has null Euler homotopy characteristic, both bounds are sharp.
Gabor filters are biologically motivated convolution kernels that have been widely used in the fi... more Gabor filters are biologically motivated convolution kernels that have been widely used in the field of computer vision and, specially, in face recognition during the last decade. This paper proposes a statistical model of Gabor coefficients extracted from face images using generalized Gaussian distributions (GGD's). By measuring the Kullback-Leibler distance (KLD) between the pdf of the GGD and the relative frequency of the coefficients, we conclude that GGD's provide an accurate modeling. The underlying statistics allow us to reduce the required amount of data to be stored (i.e. data compression) via Lloyd-Max quantization. Verification experiments on the XM2VTS database show that performance does not drop when, instead of the original data, we use quantized coefficients.
Let (ΛV,d) be the Sullivan model of a pure elliptic space S. We give an algorithm, based on the c... more Let (ΛV,d) be the Sullivan model of a pure elliptic space S. We give an algorithm, based on the computation of the Hilbert function of certain ideal, that provides a lower and an upper bound for the rational L.–S. category of S,cat0(ΛV,d). When S has null Euler homotopy characteristic, both bounds are sharp.
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