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Radial basis functions (RBFs) consist of a two-layer neural network, where each hidden unit implements a kernel function. Each kernel is associated with an activation region from the input space and its output is fed to an output unit. In order to find the parameters of a neural network which embeds this structure we take into consideration two different(More)
A new methodology for fingerprinting and watermarking three-dimensional (3-D) graphical objects is proposed in this paper. The 3-D graphical objects are described by means of polygonal meshes. The information to be embedded is provided as a binary code. A watermarking methodology has two stages: embedding and detecting the information that has been embedded(More)
This paper proposes a joint maximum likelihood and Bayesian methodology for estimating Gaussian mixture models. In Bayesian inference, the distributions of parameters are modeled, characterized by hyperparameters. In the case of Gaussian mixtures, the distributions of parameters are considered as Gaussian for the mean, Wishart for the covariance, and(More)
—This paper develops a maximum a posteriori (MAP) probability estimation framework for shape-from-shading (SFS) from synthetic aperture radar (SAR) images. The aim is to use this method to reconstruct surface topography from a single radar image of relatively complex terrain. Our MAP framework makes explicit how the recovery of local surface orientation(More)
In this paper, we present a new blind and robust 3-D mesh water-marking scheme that makes use of the recently proposed manifold harmonics analysis. The mesh spectrum coefficient amplitudes obtained by using this analysis are quite robust against various attacks, including connectivity changes. A blind 16-bit watermark is embedded through an iterative scalar(More)
Copyright protection of graphical objects and models is important for protecting author rights in animation, multimedia, computer-aided design (CAD), virtual reality, medical imaging, etc. In this paper we suggest a blind watermarking algorithm for 3D models and objects. A string of bits, generated according to a key, is embedded in the geometrical(More)
of the four problems with a perfect classification record for all bit strings of finite lengths. Induction is seen here as the process of deriving a stable metric space to separate the training groups. A stable metric space is one containing well-separated, compact clusters. From the perspectives of clustering and statistical discriminant analysis, the(More)