Adrian G. Bors

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In this paper we provide a short overview of the Radial Basis Functions (RBF), their properties, the motivations behind their use and some of their applications. RBF’s have been employed for functional approximation in time-series modeling and in pattern classification. They have been shown to implement the Bayesian rule and to model any continuous(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)
In this paper, we propose an interpolation algorithm using a mathematical morphology morphing approach. The aim of this algorithm is to reconstruct the n-dimensional object from a group of (n - 1)-dimensional sets representing sections of that object. The morphing transformation modifies pairs of consecutive sets such that they approach in shape and size.(More)
Kernel density estimation is a nonparametric procedure for probability density modeling, which has found several applications in various fields. The smoothness and modeling ability of the functional approximation are controlled by the kernel bandwidth. In this paper, we describe a Bayesian estimation method for finding the bandwidth from a given data set.(More)
Various approaches have been proposed for simultaneous optical flow estimation and segmentation in image sequences. In this study, the moving scene is decomposed into different regions with respect to their motion, by means of a pattern recognition scheme. The inputs of the proposed scheme are the feature vectors representing still image and motion(More)
In this paper, we present a new blind and robust 3-D mesh watermarking 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)
This paper describes a new statistical approach for watermarking mesh representations of 3-D graphical objects. A robust digital watermarking method has to mitigate among the requirements of watermark invisibility, robustness, embedding capacity and key security. The proposed method employs a mesh propagation distance metric procedure called the fast(More)
This paper proposes a new approach to 3D watermarking by ensuring the optimal preservation of mesh surfaces. A new 3D surface preservation function metric is defined consisting of the distance of a vertex displaced by watermarking to the original surface, to the watermarked object surface as well as the actual vertex displacement. The proposed method is(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)