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

This paper presents the concept of contact-based biometric features, which are behavioral biometric features related to the dynamic manipulation of objects that exist in the surrounding environment. The motivation behind the proposed features derives from activity-related biometrics and the extension of them to activities involving objects. The proposed approach exploits methods from different scientific fields, such as virtual reality, collision detection and pattern classification and is applicable to user authentication systems. Experimental results in a data-set of 20 subjects show that the introduced features comprise a very efficient and interesting approach in the research of biometric features.

/pdf/a-first-approach-to-contact-based-biometrics-for-user-50rkisylxy.pdf

A First Approach to Contact-Based Biometrics for User Authentication

In this paper a novel procedure for the representation of 3D surfaces using 3D hierarchical adaptive wireframes is presented. The 3D surfaces are generated by dense depth maps. The procedure is based on pyramidal analysis using the Quin-cunx Sampling Minimum Variance Interpolation (QMVINT) lters. The use of this method minimizes the variance (which is a measure of the entropy) of the interpolation error and therefore results to optimal compression of the wireframe information transmitted. At the same time, it produces a hierarchy of meshes based on quin-cunx sampling where coarse meshes are as similar to their ner versions as possible. Depending on its interpolation error and the available bitrate, each ltered sample is candidate for becoming a node of the wireframe. The result is a progressive sequence of wireframes consisting of more triangles wherever large variations in depth exist and fewer in uniform regions. Experimental results demonstrate the usage and performance of the algorithm.

/pdf/hierarchical-representation-of-surfaces-using-3d-wireframes-jikor6zsmb.pdf

Hierarchical Representation of Surfaces Using 3D Wireframes

In this paper, a novel method for Cued Speech language recognition is proposed. A multimodal processing framework is developed for the efficient fusion of the modalities under consideration. The robust feature extraction from the audio, lip shape and gesture modalities is also discussed. Moreover, the inherent correlation among the signals is modelled using a modified Coupled Hidden Markov Model. The contribution of each modality to the fused decision is modified by assessing its reliability and assigning a weighting factor to improve the accuracy of the recognized words. The method is experimentally evaluated and is shown to outperform methods that rely only on the perceivable information to infer the transmitted messages.

Multimodal fusion for cued Speech language recognition

A novel frequency domain technique for image blocking artifact reduction is presented in this paper. For each block, its DC and AC coefficients are recalculated for artifact reduction. To achieve this, a closed form representation of the optimal correction of the DCT coefficients is produced by minimizing a novel enhanced form of the Mean Squared Difference of Slope (MSDS), for every frequency separately. Experimental results illustrating the performance of the proposed method are presented and evaluated.

Reduction of blocking artifacts in block-based compressed images

We present a wavelet-based framework for the encoding of video in multiple descriptions. Using the proposed methodology, the generation of multiple descriptions is performed so that drift is eliminated at the decoder regardless of the number of received descriptions. Moreover, the proposed framework is flexible in the sense that it allows the encoding of video into an arbitrary number of descriptions. We also present a thorough analysis of rate allocation issues and propose three algorithms for the optimal allocation of redundancy. Experimental results for the transmission of video using two descriptions demonstrate the efficiency of the proposed method.

/pdf/multiple-description-wavelet-coding-of-layered-video-using-ukkna51qxp.pdf

Michael G. Strintzis

Papers

A First Approach to Contact-Based Biometrics for User Authentication

Hierarchical Representation of Surfaces Using 3D Wireframes

Multimodal fusion for cued Speech language recognition

Reduction of blocking artifacts in block-based compressed images

Multiple description wavelet coding of layered video using optimal redundancy allocation