Learn More
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)
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)
We propose a pattern classification based approach for simultaneous three-dimensional (3-D) object modeling and segmentation in image volumes. The 3-D objects are described as a set of overlapping ellipsoids. The segmentation relies on the geometrical model and graylevel statistics. The characteristic parameters of the ellipsoids and of the graylevel(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)
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)
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)
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)
—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)