Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

The bifurcational behaviour of the spatially distributed Rayleigh equation

At the present work the bifurcational behaviour of the solutions of Rayleigh equation and corresponding spatially distributed system is being analysed. The conditions of oscillatory and monotonic loss of stability are obtained. In the case of oscillatory loss of stability, the analysis of linear spectral problem is being performed. For nonlinear problem, recurrent formulas for the general term of the asymptotic approximation of the self-oscillations are found, the stability of the periodic mode is analysed. Lyapunov-Schmidt method is being used for asymptotic approximation. The correlation between periodic solutions of ODE and PDE is being investigated. The influence of the diffusion on the frequency of self-oscillations is being analysed. Several numerical experiments are being performed in order to support theoretical findings.

The analysis of bifurcations in the spatially distributed Langford system

In this thesis the bifurcational behavior of the solutions of Langford system is analysed. The equilibriums of the Langford system are found, and the stability of equilibriums is discussed. The conditions of loss of stability are found. The periodic solution of the system is approximated. We consider three types of boundary condition for Langford spatially distributed system: Neumann conditions, Dirichlet conditions and Neumann conditions with additional requirement of zero average. We apply the Lyapunov-Schmidt method to Langford spatially distributed system for asymptotic approximation of the periodic mode. We analyse the influence of the diffusion on the behavior of self-oscillations. As well in the present work we perform numerical experiments and compare it with the analytical results.

Video transcoding in a distributed cloud computing environment

Video transcoding refers to the process of converting a digital video from one format into another format. It is a compute-intensive operation. Therefore, transcoding of a large number of simultaneous video streams requires a large amount of computing resources. Moreover, to handle di erent load conditions in a cost-e cient manner, the video transcoding service should be dynamically scalable. Infrastructure as a Service Clouds currently offer computing resources, such as virtual machines, under the pay-per-use business model. Thus the IaaS Clouds can be leveraged to provide a coste cient, dynamically scalable video transcoding service. To use computing resources e ciently in a cloud computing environment, cost-e cient virtual machine provisioning is required to avoid overutilization and under-utilization of virtual machines. This thesis presents proactive virtual machine resource allocation and de-allocation algorithms for video transcoding in cloud computing. Since users' requests for videos may change at di erent times, a check is required to see if the current computing resources are adequate for the video requests. Therefore, the work on admission control is also provided. In addition to admission control, temporal resolution reduction is used to avoid jitters in a video. Furthermore, in a cloud computing environment such as Amazon EC2, the computing resources are more expensive as compared with the storage resources. Therefore, to avoid repetition of transcoding operations, a transcoded video needs to be stored for a certain time. To store all videos for the same amount of time is also not cost-e cient because popular transcoded videos have high access rate while unpopular transcoded videos are rarely accessed. This thesis provides a cost-e cient computation and storage trade-o strategy, which stores videos in the video repository as long as it is cost-e cient to store them. This thesis also proposes video segmentation strategies for bit rate reduction and spatial resolution reduction video transcoding. The evaluation of proposed strategies is performed using a message passing interface based video transcoder, which uses a coarse-grain parallel processing approach where video is segmented at group of pictures level.

Distributed document migration between ERP systems by means of messaging and event sourcing

This bachelor’s thesis, written for Lappeenranta University of Technology and implemented in a medium-sized enterprise (SME), examines a distributed document migration system. The system was created to migrate a large number of electronic documents, along with their metadata, from one document management system to another, so as to enable a rapid switchover of an enterprise resource planning systems inside the company. The paper examines, through theoretical analysis, messaging as a possible enabler of distributing applications and how it naturally fits an event based model, whereby system transitions and states are expressed through recorded behaviours. This is put into practice by analysing the implemented migration systems and how the core components, MassTransit, RabbitMQ and MongoDB, were orchestrated together to realize such a system. As a result, the paper presents an architecture for a scalable and distributed system that could migrate hundreds of thousands of documents over weekend, serving its goals in enabling a rapid system switchover.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

A distributed, cloud-ready, digital content processing and transformation platform and a specific use case

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Distributed Repositories of Medieval Calendars and Crowd-Sourcing of Transcription

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Packaging Content for Aggregated and Federated Repositories through APTrust

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Big Data Processing in the Cloud: a Hydra/Sufia Experience

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A Distributed Microservices Framework Integrating Taverna

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A museum object repository using LIDO schema

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Exit times for some processes with normally distributed noise

Denna avhandling handlar om metoder för att hitta begränsningar för det asymptotiska beteendet hos en förväntad uthoppstid från ett område omkring en xpunkt för processer som har normalfördelad störning. I huvudsak behandlas olika typer av autoregressiva processer. Fyra olika metoder används. En metod som använder principen för stora avvikelser samt en metod som jämför uthoppstiden med en återkomsttid ger övre begränsningar för den förväntade uthoppstiden. En martingalmetod och en metod för normalfördelade stokastiska variabler ger undre begränsningar. Metoderna har alla både förtjänster och nackdelar. Genom att kombinera de olika metoderna får man de bästa resultaten. Vi får fram gränsvärdet för det asymptotiska beteendet hos en uthoppstid för den multivariata autoregressiva processen, samt motsvarande gränsvärde för den univariata autoregressiva processen av ordning n.

On Distributed Storage Codes

Distributed storage systems are studied. The interest in such system has become relatively wide due to the increasing amount of information needed to be stored in data centers or different kinds of cloud systems. There are many kinds of solutions for storing the information into distributed devices regarding the needs of the system designer. This thesis studies the questions of designing such storage systems and also fundamental limits of such systems. Namely, the subjects of interest of this thesis include heterogeneous distributed storage systems, distributed storage systems with the exact repair property, and locally repairable codes. For distributed storage systems with either functional or exact repair, capacity results are proved. In the case of locally repairable codes, the minimum distance is studied. Constructions for exact-repairing codes between minimum bandwidth regeneration (MBR) and minimum storage regeneration (MSR) points are given. These codes exceed the time-sharing line of the extremal points in many cases. Other properties of exact-regenerating codes are also studied. For the heterogeneous setup, the main result is that the capacity of such systems is always smaller than or equal to the capacity of a homogeneous system with symmetric repair with average node size and average repair bandwidth. A randomized construction for a locally repairable code with good minimum distance is given. It is shown that a random linear code of certain natural type has a good minimum distance with high probability. Other properties of locally repairable codes are also studied.