Video compression techniques are commonly used to meet the increasing demands for the storage and transmission of digital video content. Popular video compression techniques such as MPEG video encoding make use of block-transform coding algorithms which are susceptible to blocking artifacts. These artifacts can be reduced using a deblocking process, of which there are many. However, those deblocking algorithms which provide noticeable improvements in visual quality also tend to be computationally expensive and unsuitable for real-time video use. This dissertation selects and examines an appropriate algorithm for real-time video deblocking applications, and describes its hardware implementation on a Altera Cyclone II FPGA. The chosen algorithm is based on the concept of shifted thresholding; it reduces computational complexity by several means, such as by using only integer arithmetic and by replacing division operations with bit shifting. The implementation leverages the reduced hardware complexity of the chosen algorithm to cost-effectively implement real-time video deblocking.

Algorithms are presented that enable the use of vector graphics representations of images in texture maps for 3D real time rendering. Vector graphics images are resolution independent and can be zoomed arbitrarily without losing detail or crispness. Many important types of images, including text and other symbolic information, are best represented in vector form. Vector graphics textures can also be used as transparency mattes to augment geometric detail in models via trim curves. Spline curves are used to represent boundaries around regions in standard vector graphics representations, such as PDF and SVG. Antialiased rendering of such content can be obtained by thresholding implicit representations of these curves. The distance function is an especially useful implicit representation. Accurate distance function computations would also allow the implementation of special effects such as embossing. Unfortunately, computing the true distance to higher order spline curves is too expensive for real time rendering. Therefore, normally either the distance is approximated by normalizing some other implicit representation or the spline curves are approximated with simpler primitives. In this thesis, three methods for rendering vector graphics textures in real time are introduced, based on various approximations of the distance computation. The first and simplest approach to the distance computation approximates curves with line segments. Unfortunately, approximation with line segments gives only C0 continuity. In order to improve smoothness, spline curves can also be approximated with circular arcs. This approximation has C1 continuity and computing the distance to a circular arc is only slightly more expensive than computing the distance to a line segment. Finally an iterative algorithm is discussed that has good performance in practice and can compute the distance to any parametrically differentiable curve (including polynomial splines of any order) robustly. This algorithm is demonstrated in the context of a system capable of real-time rendering of SVG content in a texture map on a GPU. Data structures and acceleration algorithms in the context of massively parallel GPU architectures are also discussed. These data structures and acceleration structures allow arbitrary vector content (with space-variant complexity, and overlapping regions) to be represented in a random-access texture.

Many efforts have been carried out to provide transmission reliability in the history of communication systems. As the demand for real-time applications increased, providing a reliable communication in a timely manner for such applications is strongly desired. Considering timing constraints makes the issue of achieving reliability more difficult. This thesis concentrates on providing reliability for real-time communication in embedded networks by achieving a timing analysis and using the ARQ concept. What is carried out in this thesis is providing retransmission in a real-time manner for embedded networks according to application request. The thesis work focuses on one packet retransmission over a point to point link, but the concept is rich and can be extended to cover application request in real-time embedded networks. Two methods have been fulfilled, and a simulation has been done on the timing analysis focusing on the performance in accepting real-time traffic in the form of separate channels for each application request. The protocol combines ARQ and a scheduling algorithm as a base to support retransmission for hard real-time applications in embedded networks.

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In computer science, real-time research is an interesting topic. Nowadays real-time applications are close to us in our daily life. Skype, MSN, satellite communication, automation car and Ethernet are all things related to the real-time field. Many of our computer systems are also real-time, such as RT-Linux, Windows CE. In other words, we live in a “real-time” world. However, not everyone knows much about its existence. Hence, we chose this thesis in order to take a knowledge journey in the real-time field. For an average reader, we hope to provide some basic knowledge about real-time. For a computer science student, we will try to provide a discussion on switched multi-hop network with offsets, and the influence of offsets on real-time network performance. We try to prove that offsets provide networks of high predictability and utilization because offsets adjust packet‟s sending time. A packet‟s sending time is the time when a sender/router starts to transmit a date packet. Packets are sent one after the other. Therefore, we need to lower the time interval between one packet and another. Hence, in our network model, network performance is more predictable and effective. There might be some things left to discuss in future, so we would like to receive any advice and also suggestions for future discussions.

We present a framework for generating, compressing and rendering of SurfaceLight Field (SLF) data. Our method is based on radiance data generated usingphysically based rendering methods. Thus the SLF data is generated directlyinstead of re-sampling digital photographs. Our SLF representation decouplesspatial resolution from geometric complexity. We achieve this by uniform samplingof spatial dimension of the SLF function. For compression, we use ClusteredPrincipal Component Analysis (CPCA). The SLF matrix is first clustered to lowfrequency groups of points across all directions. Then we apply PCA to eachcluster. The clustering ensures that the within-cluster frequency of data is low,allowing for projection using a few principal components. Finally we reconstructthe CPCA encoded data using an efficient rendering algorithm. Our reconstructiontechnique ensures seamless reconstruction of discrete SLF data. We applied ourrendering method for fast, high quality off-line rendering and real-time illuminationof static scenes. The proposed framework is not limited to complexity of materialsor light sources, enabling us to render high quality images describing the full globalillumination in a scene.

Radiation-hardened processors are designed to be resilient against soft errorsbut such processors are slower than Commercial Off-The-Shelf (COTS)processors as well significantly costlier. In order to mitigate the high costs,software techniques such as task re-executions must be deployed together withadequately hardened processors to provide reliability. This leads to a huge designspace comprising of the hardening level of the processors and the numberof re-executions of each task in the system. Each configuration in this designspace represents a tradeoff between processor load, reliability and costs. The reliability comes at the price of higher costs due to higher levels of hardeningand performance degradation due to hardening or due to re-executions.Thus, the tradeoffs between performance, reliability and costs must be carefullystudied. Pertinent questions that arise in such a design scenario are — (i)how many times a task must be re-executed and (ii) what should be hardeninglevel? — such that the system reliability is satisfied. In order to evaluate such tradeoffs efficiently, in this thesis, we proposenovel framework that harnesses the computational power of Graphics ProcessingUnits (GPUs). Our framework is based on a system failure probabilityanalysis that connects the probability of failure of tasks to the overall systemreliability. Based on characteristics of this probabilistic analysis as well asreal-time deadlines, we derive bounds on the design space to prune infeasiblesolutions. Finally, we illustrate the benefits of our proposed framework withseveral experiments

The presence of autonomous systems is becoming more and more common in today’s society.The contexts in which these kind of systems appear are numerous and the variations arelarge, from large and complex systems like autonomous mining platforms to smaller, moreeveryday useful systems like the self-guided vacuum cleaner. It is essential for a completelyself-supported mobile robot placed in unknown, dynamic or unstructured environments tobe able to localise itself and find its way through maps. This localisation problem is stillnot completely solved although the idea of completely autonomous systems arose in thehuman society centuries ago. Its complexity makes it a wide-spread field of reasearch evenin present days. In this work, the localisation problem is approached with an appearance based method forplace recognition. The objective is to develop an algorithm for fast pose hypotheses generationfrom a map. A database containing very low resolution images from urban environmentsis built and very short image retrieval times are made possible by application of imagedimension reduction. The evaluation of the database shows that it has real time potential becausea set of pose hypotheses can be generated in 3-25 hundreds of a second depending onthe tuning of the database. The probability of finding a correct pose suggestion among thegenerated hypotheses is as high as 87%, even when only a few hypotheses are retrieved fromthe database.

As the demand for energy increases, as well as the demand for renewable energy, Vattenfall, as network owner, receives many requests to connect new wind power to the grid. The limiting factor for how much wind power that can be connected to the grid is in this case the maximum current capacity of the overhead lines that is based on a line temperature limit. The temperature limit is set to ensure a safety distance between the lines and the ground. This master thesis project is a part of a research project at Vattenfall Research and Development that is examining the possibilities of increasing the allowed current on overhead lines in order to be able to connect more wind power to the existing network. Measured data from two overhead lines in southern Sweden is analyzed and the internal relations between the measured parameters are examined. The measured parameters are overhead line sag, line temperature, ambient temperature, solar radiation, wind speed and line current. The results indicate that there is a big load margin that could be utilized to increase the maximum current as long as further work could show that low winds at line height correlates with low wind at nacelle height. The results show that the sag versus line temperature is approximately linear within the measured temperature range. This means that a real-time-monitoring system measuring the line temperature should give adequate knowledge of the line position to ensure the safety distance. A model for the line temperature as a function of insolation, current, ambient temperature and wind speed has been estimated for one of the lines. Simulations show that a sudden increase in current at a worst-case scenario would give the operators about ten minutes to react before the line reaches the temperature limit.

The goal of this project is to implement a system to analyse an audio signal containing speech, and produce a classifcation of lip shape categories (visemes) in order to synchronize the lips of a computer generated face with the speech. The thesis describes the work to derive a method that maps speech to lip move- ments, on an animated face model, in real time. The method is implemented in C++ on the PC/Windows platform. The program reads speech from pre-recorded audio files and continuously performs spectral analysis of the speech. Neural networks are used to classify the speech into a sequence of phonemes, and the corresponding visemes are shown on the screen. Some time delay between input speech and the visualization could not be avoided, but the overall visual impression is that sound and animation are synchronized.