Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Information-hiding techniques have recently become important in a number of application areas. Digital audio, video, and pictures are increasingly furnished with distinguishing but imperceptible marks, which may contain a hidden copyright notice or serial number or even help to prevent unauthorized copying directly. Military communications systems make increasing use of traffic security techniques which, rather than merely concealing the content of a message using encryption, seek to conceal its sender, its receiver, or its very existence. Similar techniques are used in some mobile phone systems and schemes proposed for digital elections. Criminals try to use whatever traffic security properties are provided intentionally or otherwise in the available communications systems, and police forces try to restrict their use. However, many of the techniques proposed in this young and rapidly evolving field can trace their history back to antiquity, and many of them are surprisingly easy to circumvent. In this article, we try to give an overview of the field, of what we know, what works, what does not, and what are the interesting topics for research.

/pdf/information-hiding-a-survey-wve0ipfu9n.pdf

Information hiding-a survey

Stable non-Gaussian random processes , by G. Samorodnitsky and M. S. Taqqu. Pp. 632. £49.50. 1994. ISBN 0-412-05171-0 (Chapman and Hall).

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

This article reviews the requirements for successful compressed sensing (CS), describes their natural fit to MRI, and gives examples of four interesting applications of CS in MRI. The authors emphasize on an intuitive understanding of CS by describing the CS reconstruction as a process of interference cancellation. There is also an emphasis on the understanding of the driving factors in applications, including limitations imposed by MRI hardware, by the characteristics of different types of images, and by clinical concerns.

/pdf/compressed-sensing-mri-2wgw41cvre.pdf

Compressed Sensing MRI

In this paper, an ontology-driven approach for the semantic analysis of video is proposed. This approach builds on an ontology infrastructure and in particular a multimedia ontology that is based on the notions of Visual Information Object (VIO) and Multimedia Information Object (MMIO). The latter constitute extensions of the Information Object (IO) design pattern, previously proposed for refining and extending the DOLCE core ontology. This multimedia ontology, along with the more domain-specific parts of the developed knowledge infrastructure, supports the analysis of video material, models the content layer of video, and defines generic as well as domain-specific concepts whose detection is important for the analysis and description of video of the specified domain. The signal-level video processing that is necessary for linking the developed ontology infrastructure with the signal domain includes the combined use of a temporal and a spatial segmentation algorithm, a layered structure of Support Vector Machines (SVMs)-based classifiers and a classifier fusion mechanism. A Genetic Algorithm (GA) is introduced for optimizing the performed information fusion step. These processing methods support the decomposition of visual information, as specified by the multimedia ontology, and the detection of the defined domain-specific concepts that each piece of video signal, treated as a VIO, is related to. Experimental results in the domain of disaster news video demonstrate the efficiency of the proposed approach.

/pdf/ontology-driven-semantic-video-analysis-using-visual-4f30reychp.pdf

Ontology-driven semantic video analysis using visual information objects

A system for building a three dimensional (3-D) human head model from two camera views is proposed. A generic 3-D face model is adapted to a human face of which the frontal and profile views are given. Then, a 3-D ellipsoid approximation technique is used to fit an ellipsoid to the 3-D wireframe model. This ellipsoid is then used to approximate the back of the head, while the the initial 3-D face model provides information for the high-detail front part of the head. The part of the ellipsoid model that corresponds to the back of the head is then identified and an algorithm to merge the front (face) and the back part is proposed. A cylindrical texture map is finally built covering the entire area of the head by exploiting the inherent face symmetry. The final result is a complete, textured model of a specific person's head.

Generation of 3-D head models from multiple images using ellipsoid approximation for the rear part

This paper addresses the problem of face recognition in the presence of facial deformations caused by expressions. An isometric mapping between surfaces is assumed, which allows preservation of geodesic distance between facial points. Subject to this assumption, we propose a novel technique which integrates 2D and 3D information to establish a new deformation invariant representation of the face. The 3D surface is used to define a polar geodesic coordinate space which is independent of the intrinsic geometry of the face. The corresponding color image is embedded in this space and serves as the recognition data. A preceding stage of hierarchical diffeomorphic grid-based image warping before the recognition process combined with a lip segmentation technique are also employed to increase the overall performance of the algorithm.

Expression Compensation for Face Recognition Using a Polar Geodesic Representation

In this paper, we present a technique for addressing 3-dimensional face recognition in presence of facial expressions using a bilinear model. The bilinear model allows decoupling the impact of identity and expression on face appearance and encoding their contribution in separate control parameters. This is achieved by first representing faces as parametric surface models described by a fixed length parameter vector. A generic face model is fitted to each face based on a novel technique that relies on geodesic distances to find implicitly corresponding facial landmarks between the model and the face in hand. Model parameters are then used for bilinear decomposition. The experimental results on the publicly available BU-3DFE face database demonstrate the effectiveness of our technique.

Expression-Compensated 3D Face Recognition with Geodesically Aligned Bilinear Models

This document presents an approach for generating VRML animation sequences from Sign Language notation, based on MPEG-4 Face and Body Animation. The proposed application aims in providing a computer-based sign-language synthesis output for the deaf and the hearing impaired. Moreover the application may be used as a teaching tool for relatives of deaf people as well as people interested in learning the sign language. The application receives text sentences as input and provides as output 3D animated VRML sequences able to be visualised in any VRML-compliant browser.

/pdf/text-to-sign-language-synthesis-tool-4ppjndvf84.pdf

Michael G. Strintzis

Papers

Ontology-driven semantic video analysis using visual information objects

Generation of 3-D head models from multiple images using ellipsoid approximation for the rear part

Expression Compensation for Face Recognition Using a Polar Geodesic Representation

Expression-Compensated 3D Face Recognition with Geodesically Aligned Bilinear Models

Text-to-sign language synthesis tool