This masters thesis proposes that multimodal behaviour generation frameworks are an appropriate way to increase the believability of animated characters in virtual heritage applications. To investigate this proposal, an existing virtual museum guide application developed by the author is extended by integrating the Behavioural Markup Language (BML), and the open-source BML realiser SmartBody. The architectural and implementation decisions involved in this process are catalogued and discussed. The integration of BML and SmartBody results in a dramatic improvement in the quality of character animation in the application, as well as greater flexibility and extensibility, including the ability to create scripted sequences of behaviour for multiple characters in the virtual museum. The successful integration confirms that multimodal behaviour generation frameworks have a place in virtual heritage applications.

The gameplay of real-time strategy games can be divided into macromanagement and micromanagement. Several researchers have studied automated learning for macromanagement, using a case-based reasoning/reinforcement learning architecture to defeat both static and dynamic opponents. Unlike the previous research, we present the Unit Priority Artificial Intelligence (UPAI). UPAI is a case-based reasoning/reinforcement learning system for learning the micromanagement task of prioritizing which enemy units to attack in different game situations, through unsupervised learning from experience. We discuss different case representations, as well as the exploration vs exploitation aspect of reinforcement learning in UPAI. Our research demonstrates that UPAI can learn to improve its micromanagement decisions, by defeating both static and dynamic opponents in a micromanagement setting.

Coupling commodity CPUs and modern GPUs give you heterogeneous systems that are cheap, high-performance with incredible FLOPS counts. Recent evolution of GPGPU models and technologies make these systems even more appealing as compute devices for a range of HPC applications including image processing, seismic processing and other physical modeling, as well as linear programming applications. In fact, graphics vendor such as NVIDIA and AMD are now targeting HPC with some of their products. Due to the power and frequency walls, the trend is now to use multiple GPUs on a given system, much like you will find multiple cores on CPU-based systems. However, increasing the hierarchy of resource wides the spectrum of factors that may impact on the performance of the system. The lack of good models for GPU-based, heterogeneous systems also makes it harder to understand which factors impact performance the most. The goal of this thesis is to analyze such factors by investigating and benchmarking NVIDIA's multi-GPU solution, their recent NVIDIA Tesla S1070 Computing System. This system combines four T10 GPUs making available up to 4 TFLOPS of computational power. Based on a comparative study of fundamental parallel computing models and on the specific heterogeneous features exposed by the system, we define a test space for performance analysis. As a case study, we develop a red-black, SOR PDE solver for Laplace equations with Dirichlet boundaries, well known for requiring constant communication in order to exchange neighboring data. To aid both design and analysis, we propose a model for multi-GPU systems targeting communication between the several GPUs. The main variables exposed by the benchmark application are: domain size and shape, kind of data partitioning, number of GPUs, width of the borders to exchange, kernels to use, and kind of synchronization between the GPU contexts. Among other results, the framework is able to point out the most critical bounds of the S1070 system when dealing with applications like the one in our case study. We show that the multi-GPU system greatly benefits from using all its four GPUs on very large data volumes. Our results show the four GPUs almost four times faster than a single GPU, and twice as fast as two. Our analysis outcomes also allow us to refine our static communication model, enriching it with regression-based predictions.

Medical ultrasound imaging is a great diagnostic tool for physicians because of its noninvasive nature. It is performed by directing ultrasonic sound into tissue and visualizing the echo signal. Aberration in the reflected signal is caused by inhomogeneous tissue varying the speed of sound, which results in a blurring of the image. Dr. Måsøy and Dr. Varslot at NTNU have developed and algorithm for estimating and correcting ultrasound aberration. This algorithm adaptively estimates the aberration and adjusts the next transmitted signal to account for the aberration, resulting in a clearer image. This master's thesis focuses on developing a parallelized version of this algorithm. Since NVIDIA CUDA (Compute Unified Device Architecture) is an architecture oriented towards general purpose computations on the GPU (Graphics Processing Unit), it also examines how suitable the parallelization is for modern GPUs. The goal is using the GPU to off-load the CPU with an aim of achieving real-time calculations of the correction filter. The ultrasound image creation is examined, including how the aberrations come into being. Next, how the algorithm can be implemented efficiently using the GPU is looked at using both NVIDIA's FFT (fast Fourier transform) library as well as developing several computational kernels to run on the GPU. Our findings show that the algorithm is highly parallelizable and achieves a speedup of over 5x when implemented on the GPU. This is, however, not fast enough for real-time correction, but taking into account suggestions for overcoming the limitations encountered, the study shows great promise for future work.

Linear programming is a form of mathematical optimisation in which one seeks to optimise a linear function subject to linear constraints on the variables. It is a very versatile tool that has many important applications, one of them being modelling of production and trade in the petroleum industry. The Cell Broadband Engine, developed by IBM, Sony and Toshiba, is an innovative multicore architecture that has already been proven to have a great potential for high performance computing. However, developing applications for the Cell/BE is challenging, particularily due to the low-level memory management that is mandated by the architecture, and because careful optimisation by hand is often required to get the most out of the hardware. In this thesis, we investigate the opportunities for implementing a parallel solver for sparse linear programs on the Cell/BE. A parallel version of the standard simplex method is developed, and the ASYNPLEX algorithm by Hall and McKinnon is partially implemented on the Cell/BE. We have met substantial challenges when it comes to numerical stability, and this has prevented us from spending sufficient time on Cell/BE-specific optimisation and support for large data sets. Our implementations can therefore only be regarded as proofs of concept, but we provide analyses and discussions of several aspects of the implementations, which may guide the future work on this topic.

The structure of XML documents can be used by search engines to answer structured queries or to provide better relevancy. Several index structures exist for search in XML data. This study focuses on inverted lists with dictionary coded path types and dewey coded path instances. The dewey coded path index is large, but could be compressed. This study examines query processing with indexes encoded using well known integer coding methods VByte and PFor(delta) and methods tailored for the dewey index. Intersection queries and structural queries are evaluated. In addition to standard document level skipping, skip operations for path types are implemented and evaluated. Four extensions over plain PFor methods are proposed and tested. Path type sorting sorts dewey codes on their path types and store all deweys from one path type together. Column wise dewey storage stores the deweys in columns instead of rows. Prefix coding a well known method, is adapted to the column wise dewey storage, and dynamic column wise method chooses between row wise and column wise storage based on the compressed data. Experiments are performed on a XML collection based on Wikipedia. Queries are generated from the TREC 06 efficiency task query trace. Several different types of structural queries have been executed. Experiments show that column wise methods perform good on both intersection and structural queries. The dynamic column wise scheme is in most cases the best, and creates the smallest index. Special purpose skipping for path types makes some queries extremely fast and can be implemented with only limited storage footprint. The performance of in-memory search with multi-threaded query execution is limited by memory bandwidth.

This report deals with edge and line detection in pictures with complicated and/or blurred objects. It explores the alternatives available, in edge detection, edge linking and object recognition. Choice of methods are the Canny edge detection and Local edge search processing combined with regional edge search processing in the form of polygon approximation.

This master's thesis explores the world of multi-touch interaction with gesture recognition. The focus is on camera based multi-touch techniques, as these provide a new dimension to multi-touch with its ability to recognize objects. During the project, a multi-touch table based on the technology Diffused Surface Illumination has been built. In addition to building a table, a complete gesture recognition system has been implemented, and different gesture recognition algorithms have been successfully tested in a multi-touch environment. The goal with this table, and the accompanying gesture recognition system, is to create an open and affordable multi-touch solution, with the purpose of bringing multi-touch out to the masses. By doing this, more people will be able to enjoy the benefits of a more natural interaction with computers. In a larger perspective, multi-touch is just the beginning, and by adding additional modalities to our applications, such as speech recognition and full body tracking, a whole new level of computer interaction will be possible.

This report describes a stereo vision system to be used on a mobile robot. The system is able to triangulate the positions of cylindrical and spherical objects in a 3D environment. Triangulation is done in real-time by matching regions in two images, and calculating the disparities between them.

This report is about computer game based learning, how to make a program for making educational games, the possibilities to use a hypermedia structure for storage of the data in an educational game, and different learning theories related to computer game based learning. The first part is about the different learning theories behaviourism, cognitivism, constructivism, socio-constructivism, and situated learning. The different theories are related to learning games, and a classification of game based learning is also given. Hypermedia is a smart and efficient way of organizing data, and is a relevant solution for use in education and games. The relationship between data, information and wisdom is central, and how the hypermedia base is constructed and different information structures are described. The advantages and limitations of use of hypermedia in education are discussed, and examples of use, as in OPSYS and the Mobile instruction system, are given. There exist some computer games for use in higher education, and some of them are described. To make a good educational, many certain requirements have to be fulfilled both aspects in game design and learning aspects. The main part of the report is about the Educational Game Editor. The idea is to design a program for making computer games for use in education. Before the design, the Software Requirements Specification is presented, containing functional and quality requirements, and scenarios to exemplify the requirements. The conceptual design of the program gives an overall description and describes the phases of creating a game and the elements the game consists of: file management, object management, Library, and Tools. The main architectural drivers are usability and availability. The program must be easy to use and be stable and not crash. An example of making a simple game about the history of Trondheim explains how to use the program in steps, and gives a good guide for the users to make their own game.