Statistical motion learning for improved transform domain Wyner-Ziv video coding

Wyner - Ziv (WZ) video coding is a particular case of distributed video coding (DVC), the recent video coding paradigm based on the Slepian - Wolf and Wyner - Ziv theorems which exploits the source temporal correlation at the decoder and not at the encoder as in predictive video coding. Although some progress has been made in the last years, WZ video coding is still far from the compression performance of predictive video coding, especially for high and complex motion contents. The WZ video codec adopted in this study is based on a transform domain WZ video coding architecture with feedback channel-driven rate control, whose modules have been improved with some recent coding tools. This study proposes a novel motion learning approach to successively improve the rate-distortion (RD) performance of the WZ video codec as the decoding proceeds, making use of the already decoded transform bands to improve the decoding process for the remaining transform bands. The results obtained reveal gains up to 2.3 dB in the RD curves against the performance for the same codec without the proposed motion learning approach for high motion sequences and long group of pictures (GOP) sizes.

Advanced side information creation techniques and framework for Wyner-Ziv video coding

Recently, several distributed video coding (DVC) solutions based on the distributed source coding (DSC) paradigm have appeared in the literature. Wyner-Ziv (WZ) video coding, a particular case of DVC where side information is made available at the decoder, enable to achieve a flexible distribution of the computational complexity between the encoder and decoder, promising to fulfill novel requirements from applications such as video surveillance, sensor networks and mobile camera phones. The quality of the side information at the decoder has a critical role in determining the WZ video coding rate-distortion (RD) performance, notably to raise it to a level as close as possible to the RD performance of standard predictive video coding schemes. Towards this target, efficient motion search algorithms for powerful frame interpolation are much needed at the decoder. In this paper, the RD performance of a Wyner-Ziv video codec is improved by using novel, advanced motion compensated frame interpolation techniques to generate the side information. The development of these type of side information estimators is a difficult problem in WZ video coding, especially because the decoder only has available some reference, decoded frames. Based on the regularization of the motion field, novel side information creation techniques are proposed in this paper along with a new frame interpolation framework able to generate higher quality side information at the decoder. To illustrate the RD performance improvements, this novel side information creation framework has been integrated in a transform domain turbo coding based Wyner-Ziv video codec. Experimental results show that the novel side information creation solution leads to better RD performance than available state-of-the-art side information estimators, with improvements up to 2 dB: moreover, it allows outperforming H.264/AVC Intra by up to 3 dB with a lower encoding complexity.

Augmented LDPC Graph for Distributed Video Coding with Multiple Side Information

The advances made in channel-capacity codes, such as turbo codes and low-density parity-check (LDPC) codes, have played a major role in the emerging distributed source coding paradigm. LDPC codes can be easily adapted to new source coding strategies due to their natural representation as bipartite graphs and the use of quasi-optimal decoding algorithms, such as belief propagation. This paper tackles a relevant scenario in distributedvideo coding: lossy source coding when multiple side information (SI) hypotheses are available at the decoder, each one correlated with the source according to different correlation noise channels. Thus, it is proposed to exploit multiple SI hypotheses through an efficient joint decoding technique withmultiple LDPC syndrome decoders that exchange information to obtain coding efficiency improvements. At the decoder side, the multiple SI hypotheses are created with motion compensated frame interpolation and fused together in a novel iterative LDPC based Slepian-Wolf decoding algorithm. With the creation of multiple SI hypotheses and the proposed decoding algorithm, bitrate savings up to 8.0% are obtained for similar decoded quality.

Side information creation for efficient Wyner-Ziv video coding: Classifying and reviewing

Video coding technologies have played a major role in the explosion of large market digital video applications and services. In this context, the very popular MPEG-x and H-26x video coding standards adopted a predictive coding paradigm, where complex encoders exploit the data redundancy and irrelevancy to 'control' much simpler decoders. This codec paradigm fits well applications and services such as digital television and video storage where the decoder complexity is critical, but does not match well the requirements of emerging applications such as visual sensor networks where the encoder complexity is more critical. The Slepian Wolf and Wyner-Ziv theorems brought the possibility to develop the so-called Wyner-Ziv video codecs, following a different coding paradigm where it is the task of the decoder, and not anymore of the encoder, to (fully or partly) exploit the video redundancy. Theoretically, Wyner-Ziv video coding does not incur in any compression performance penalty regarding the more traditional predictive coding paradigm (at least for certain conditions). In the context of Wyner-Ziv video codecs, the so-called side information, which is a decoder estimate of the original frame to code, plays a critical role in the overall compression performance. For this reason, much research effort has been invested in the past decade to develop increasingly more efficient side information creation methods. This paper has the main objective to review and evaluate the available side information methods after proposing a classification taxonomy to guide this review, allowing to achieve more solid conclusions and better identify the next relevant research challenges. After classifying the side information creation methods into four classes, notably guess, try, hint and learn, the review of the most important techniques in each class and the evaluation of some of them leads to the important conclusion that the side information creation methods provide better rate-distortion (RD) performance depending on the amount of temporal correlation in each video sequence. It became also clear that the best available Wyner-Ziv video coding solutions are almost systematically based on the learn approach. The best solutions are already able to systematically outperform the H.264/AVC Intra, and also the H.264/AVC zero-motion standard solutions for specific types of content. (C) 2013 Elsevier B.V. All rights reserved.

Correlation modeling for a distributed scalable video codec based on the HEVC standard

The growing heterogeneity of networks, devices and consumption conditions asks for flexible and adaptive video coding solutions. The compression power of the HEVC standard and the benefits of the distributed video coding paradigm allow designing novel scalable coding solutions with improved error robustness and low encoding complexity while still achieving competitive compression efficiency. In this context, this paper proposes a novel scalable video coding scheme using a HEVC Intra compliant base layer and a distributed coding approach in the enhancement layers (EL). This design inherits the HEVC compression efficiency while providing low encoding complexity at the enhancement layers. The temporal correlation is exploited at the decoder to create the EL side information (SI) residue, an estimation of the original residue. The EL encoder sends only the data that cannot be inferred at the decoder, thus exploiting the correlation between the original and SI residues; however, this correlation must be characterized with an accurate correlation model to obtain coding efficiency improvements. Therefore, this paper proposes a correlation modeling solution to be used at both encoder and decoder, without requiring a feedback channel. Experiments results confirm that the proposed scalable coding scheme has lower encoding complexity and provides BD-Rate savings up to 3.43% in comparison with the HEVC Intra scalable extension under development. © 2014 IEEE.

Perceptually driven video error protection using a distributed source coding approach

In video communication systems, the video signals are typically compressed and sent to the decoder through an error-prone transmission channel that may corrupt the compressed signal, causing the degradation of the final decoded video quality. In this context, it is possible to enhance the error resilience of typical predictive video coding schemes using as inspiration principles and tools from an alternative video coding approach, the so-called Distributed Video Coding (DVC), based on the Distributed Source Coding (DSC) theory. Further improvements in the decoded video quality after error-prone transmission may also be obtained by considering the perceptual relevance of the video content, as distortions occurring in different regions of a picture have a different impact on the user's final experience. In this context, this paper proposes a Perceptually Driven Error Protection (PDEP) video coding solution that enhances the error resilience of a state-of-the-art H.264/AVC predictive video codec using DSC principles and perceptual considerations. To increase the H.264/AVC error resilience performance, the main technical novelties brought by the proposed video coding solution are: (i) design of an improved compressed domain perceptual classification mechanism; (ii) design of an improved transcoding tool for the DSC-based protection mechanism; and (iii) integration of a perceptual classification mechanism in an H.264/AVC compliant codec with a DSC-based error protection mechanism. The performance results obtained show that the proposed PDEP video codec provides a better performing alternative to traditional error protection video coding schemes, notably Forward Error Correction (FEC)-based schemes. (C) 2013 Elsevier B.V. All rights reserved.

An example-based generator of XSLT programs

XSLT is a powerful and widely used language for transforming XML documents. However, its power and complexity can be overwhelming for novice or infrequent users, many of whom simply give up on using this language. On the other hand, many XSLT programs of practical use are simple enough to be automatically inferred from examples of source and target documents. An inferred XSLT program is seldom adequate for production usage but can be used as a skeleton of the final program, or at least as scaffolding in the process of coding it. It should be noted that the authors do not claim that XSLT programs, in general, can be inferred from examples. The aim of Vishnu—the XSLT generator engine described in this chapter—is to produce XSLT programs for processing documents similar to the given examples and with enough readability to be easily understood by a programmer not familiar with the language. The architecture of Vishnu is composed by a graphical editor and a programming engine. In this chapter, the authors focus on the editor as a GWT Web application where the programmer loads and edits document examples and pairs their content using graphical primitives. The programming engine receives the data collected by the editor and produces an XSLT program.

Verificación Formal de Sistemas basada Formal Software Verification based on Automated Analysisen Análisis Automático.

Identificación y caracterización del problema. Uno de los problemas más importantes asociados con la construcción de software es la corrección del mismo. En busca de proveer garantías del correcto funcionamiento del software, han surgido una variedad de técnicas de desarrollo con sólidas bases matemáticas y lógicas conocidas como métodos formales. Debido a su naturaleza, la aplicación de métodos formales requiere gran experiencia y conocimientos, sobre todo en lo concerniente a matemáticas y lógica, por lo cual su aplicación resulta costosa en la práctica. Esto ha provocado que su principal aplicación se limite a sistemas críticos, es decir, sistemas cuyo mal funcionamiento puede causar daños de magnitud, aunque los beneficios que sus técnicas proveen son relevantes a todo tipo de software. Poder trasladar los beneficios de los métodos formales a contextos de desarrollo de software más amplios que los sistemas críticos tendría un alto impacto en la productividad en tales contextos. Hipótesis. Contar con herramientas de análisis automático es un elemento de gran importancia. Ejemplos de esto son varias herramientas potentes de análisis basadas en métodos formales, cuya aplicación apunta directamente a código fuente. En la amplia mayoría de estas herramientas, la brecha entre las nociones a las cuales están acostumbrados los desarrolladores y aquellas necesarias para la aplicación de estas herramientas de análisis formal sigue siendo demasiado amplia. Muchas herramientas utilizan lenguajes de aserciones que escapan a los conocimientos y las costumbres usuales de los desarrolladores. Además, en muchos casos la salida brindada por la herramienta de análisis requiere cierto manejo del método formal subyacente. Este problema puede aliviarse mediante la producción de herramientas adecuadas. Otro problema intrínseco a las técnicas automáticas de análisis es cómo se comportan las mismas a medida que el tamaño y complejidad de los elementos a analizar crece (escalabilidad). Esta limitación es ampliamente conocida y es considerada crítica en la aplicabilidad de métodos formales de análisis en la práctica. Una forma de atacar este problema es el aprovechamiento de información y características de dominios específicos de aplicación. Planteo de objetivos. Este proyecto apunta a la construcción de herramientas de análisis formal para contribuir a la calidad, en cuanto a su corrección funcional, de especificaciones, modelos o código, en el contexto del desarrollo de software. Más precisamente, se busca, por un lado, identificar ambientes específicos en los cuales ciertas técnicas de análisis automático, como el análisis basado en SMT o SAT solving, o el model checking, puedan llevarse a niveles de escalabilidad superiores a los conocidos para estas técnicas en ámbitos generales. Se intentará implementar las adaptaciones a las técnicas elegidas en herramientas que permitan su uso a desarrolladores familiarizados con el contexto de aplicación, pero no necesariamente conocedores de los métodos o técnicas subyacentes. Materiales y métodos a utilizar. Los materiales a emplear serán bibliografía relevante al área y equipamiento informático. Métodos. Se emplearán los métodos propios de la matemática discreta, la lógica y la ingeniería de software. Resultados esperados. Uno de los resultados esperados del proyecto es la individualización de ámbitos específicos de aplicación de métodos formales de análisis. Se espera que como resultado del desarrollo del proyecto surjan herramientas de análisis cuyo nivel de usabilidad sea adecuado para su aplicación por parte de desarrolladores sin formación específica en los métodos formales utilizados. Importancia del proyecto. El principal impacto de este proyecto será la contribución a la aplicación práctica de técnicas formales de análisis en diferentes etapas del desarrollo de software, con la finalidad de incrementar su calidad y confiabilidad. A crucial factor for software quality is correcteness. Traditionally, formal approaches to software development concentrate on functional correctness, and tackle this problem basically by being based on well defined notations founded on solid mathematical grounds. This makes formal methods better suited for analysis, due to their precise semantics, but they are usually more complex, and require familiarity and experience with the manipulation of mathematical definitions. So, their acceptance by software engineers is rather restricted, and formal methods applications have been confined to critical systems. Nevertheless, it is obvious that the advantages that formal methods provide apply to any kind of software system. It is accepted that appropriate software tool support for formal analysis is essential, if one seeks providing support for software development based on formal methods. Indeed, some of the relatively recent sucesses of formal methods are accompanied by good quality tools that automate powerful analysis mechanisms, and are even integrated in widely used development environments. Still, most of these tools either concentrate on code analysis, and in many cases are still far from being simple enough to be employed by software engineers without experience in formal methods. Another important problem for the adoption of tool support for formal methods is scalability. Automated software analysis is intrinsically complex, and thus techniques do not scale well in the general case. In this project, we will attempt to identify particular modelling, design, specification or coding activities in software development processes where to apply automated formal analysis techniques. By focusing in very specific application domains, we expect to find characteristics that might be exploited to increase the scalability of the corresponding analyses, compared to the general case.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

Emerging roles of non-coding RNAs in pancreatic β-cell function and dysfunction.

Pancreatic β-cells play a central role in glucose homeostasis by tightly regulating insulin release according to the organism's demand. Impairment of β-cell function due to hostile environment, such as hyperglycaemia and hyperlipidaemia, or due to autoimmune destruction of β-cells, results in diabetes onset. Both environmental factors and genetic predisposition are known to be involved in the development of the disease, but the exact mechanisms leading to β-cell dysfunction and death remain to be characterized. Non-coding RNA molecules, such as microRNAs (miRNAs), have been suggested to be necessary for proper β-cell development and function. The present review aims at summarizing the most recent findings about the role of non-coding RNAs in the control of β-cell functions and their involvement in diabetes. We will also provide a perspective view of the future research directions in the field of non-coding RNAs. In particular, we will discuss the implications for diabetes research of the discovery of a new communication mechanism based on cell-to-cell miRNA transfer. Moreover, we will highlight the emerging interconnections between miRNAs and epigenetics and the possible role of long non-coding RNAs in the control of β-cell activities.

Everybody active, every day: An evidence-based approach to physical activity

‘Everybody active, every day’ is a national, evidence-based approach to support all sectors to embed physical activity into the fabric of daily life and make it an easy, cost-effective and ‘normal’ choice in every community in England.PHE has co-produced the framework with over 1,000 national and local leaders in physical activity and is calling for action from providers and commissioners in: health, social care, transportation, planning, education, sport and leisure, culture, the voluntary and community sector, as well as public and private employers.To make active lifestyles a reality for all, the framework’s 4 areas for action will:change the social ‘norm’ to make physical activity the expectationdevelop expertise and leadership within professionals and volunteerscreate environments to support active livesidentify and up-scale successful programmes nationwide‘Everybody active, every day’ is part of the cross-government ‘Moving More, Living More’ campaign for a more active nation as part of the 2012 Olympic and Paralympic Games legacy.

Ethnicity Coding

The incidence, prevalence, and mortality of many diseases are known to vary by ethnic group.There are well documented inequities in access to prevention, treatment, and palliative health and social care services based on ethnic group. There are, too, reported differences in the quality of services received by different ethnic groups and of outcomes of treatment and care. Many of these inequities are amenable to change. However, in order to address them they must, first of all, be comprehensively defined and documented. Mainstreaming ethnic monitoring/data collection is a vital step in the process. The history of such data collection in the NHS is poor, whichever of the key datasets is examined: hospital episode statistics, general practitioner data, cancer registrations, and disease registers. While steps are now being taken to remedy some of these deficiencies, the continued non-availability of ethnic monitoring data and in some cases of compatible ethnically-coded denominator data remains a problem. In particular the lack of ethnic group in births and deaths data has been the subject of widespread comment by specialists in demography and public health and is probably the single action that could most improve the evidence based for addressing ethnic/racial inequalities in health and health care.

Determinants of the educational use of digital learning materials: The mediating role of self-efficacy, perceived norm and attitude

Initiatives to stimulate the development and propagation of open educational resources (OER) need a sufficiently large community that can be mobilized to participate in this endeavour. Failure to achieve this could lead to underuse of OER. In the context of the Wikiwijs initiative a large scale survey was undertaken amongst primary and secondary school teachers to explore possible determinants of the educational use of digital learning materials (DLMs). Basing on the Integrative Model of Behaviour Prediction it was conjectured that self-efficacy, attitude and perceived norm would take a central role in explaining the intention to use DLMs. Several other predictors were added to the model as well whose effects were hypothesized to be mediated by the three central variables.All conjectured relationships were found using path analysis on survey data from 1484 teachers. Intention to DLMs was most strongly determined by self-efficacy, followed by attitude. ICT proficiency was in its turn the strongest predictor of self-efficacy. Perceived norm played only a limited role in the intention to use DLMs. Concluding, it seems paramount for the success of projects such as Wikiwijs to train teachers in the use of digital learning materials and ICT (e.g. the digital blackboard) and to impact on their attitude.

A new optimised De Bruijn coding strategy for structured light patterns

Coded structured light is an optical technique based on active stereovision that obtains the shape of objects. One shot techniques are based on projecting a unique light pattern with an LCD projector so that grabbing an image with a camera, a large number of correspondences can be obtained. Then, a 3D reconstruction of the illuminated object can be recovered by means of triangulation. The most used strategy to encode one-shot patterns is based on De Bruijn sequences. In This work a new way to design patterns using this type of sequences is presented. The new coding strategy minimises the number of required colours and maximises both the resolution and the accuracy

Disease identification based on ambulatory drugs dispensation and in-hospital ICD-10 diagnoses: a comparison.

BACKGROUND: Pharmacy-based case mix measures are an alternative source of information to the relatively scarce outpatient diagnoses data. But most published tools use national drug nomenclatures and offer no head-to-head comparisons between drugs-related and diagnoses-based categories. The objective of the study was to test the accuracy of drugs-based morbidity groups derived from the World Health Organization Anatomical Therapeutic Chemical Classification of drugs by checking them against diagnoses-based groups. METHODS: We compared drugs-based categories with their diagnoses-based analogues using anonymous data on 108,915 individuals insured with one of four companies. They were followed throughout 2005 and 2006 and hospitalized at least once during this period. The agreement between the two approaches was measured by weighted kappa coefficients. The reproducibility of the drugs-based morbidity measure over the 2 years was assessed for all enrollees. RESULTS: Eighty percent used a drug associated with at least one of the 60 morbidity categories derived from drugs dispensation. After accounting for inpatient under-coding, fifteen conditions agreed sufficiently with their diagnoses-based counterparts to be considered alternative strategies to diagnoses. In addition, they exhibited good reproducibility and allowed prevalence estimates in accordance with national estimates. For 22 conditions, drugs-based information identified accurately a subset of the population defined by diagnoses. CONCLUSIONS: Most categories provide insurers with health status information that could be exploited for healthcare expenditure prediction or ambulatory cost control, especially when ambulatory diagnoses are not available. However, due to insufficient concordance with their diagnoses-based analogues, their use for morbidity indicators is limited.