This work focuses on analysing and improving feature detection and matching. After creating an initial framework of study, four main areas of work are researched. These areas make up the main chapters within this thesis and focus on using the Scale Invariant Feature Transform (SIFT).The preliminary analysis of the SIFT investigates how this algorithm functions. Included is an analysis of the SIFT feature descriptor space and an investigation into the noise properties of the SIFT. It introduces a novel use of the a contrario methodology and shows the success of this method as a way of discriminating between images which are likely to contain corresponding regions from images which do not. Parameter analysis of the SIFT uses both parameter sweeps and genetic algorithms as an intelligent means of setting the SIFT parameters for different image types utilising a GPGPU implementation of SIFT. The results have demonstrated which parameters are more important when optimising the algorithm and the areas within the parameter space to focus on when tuning the values. A multi-exposure, High Dynamic Range (HDR), fusion features process has been developed where the SIFT image features are matched within high contrast scenes. Bracketed exposure images are analysed and features are extracted and combined from different images to create a set of features which describe a larger dynamic range. They are shown to reduce the effects of noise and artefacts that are introduced when extracting features from HDR images directly and have a superior image matching performance. The final area is the development of a novel, 3D-based, SIFT weighting technique which utilises the 3D data from a pair of stereo images to cluster and class matched SIFT features. Weightings are applied to the matches based on the 3D properties of the features and how they cluster in order to attempt to discriminate between correct and incorrect matches using the a contrario methodology. The results show that the technique provides a method for discriminating between correct and incorrect matches and that the a contrario methodology has potential for future investigation as a method for correct feature match prediction.

The rapid growth of the Internet and the advancements of the Web technologies have made it possible for users to have access to large amounts of on-line music data, including music acoustic signals, lyrics, style/mood labels, and user-assigned tags. The progress has made music listening more fun, but has raised an issue of how to organize this data, and more generally, how computer programs can assist users in their music experience. An important subject in computer-aided music listening is music retrieval, i.e., the issue of efficiently helping users in locating the music they are looking for. Traditionally, songs were organized in a hierarchical structure such as genre->artist->album->track, to facilitate the users’ navigation. However, the intentions of the users are often hard to be captured in such a simply organized structure. The users may want to listen to music of a particular mood, style or topic; and/or any songs similar to some given music samples. This motivated us to work on user-centric music retrieval system to improve users’ satisfaction with the system. The traditional music information retrieval research was mainly concerned with classification, clustering, identification, and similarity search of acoustic data of music by way of feature extraction algorithms and machine learning techniques. More recently the music information retrieval research has focused on utilizing other types of data, such as lyrics, user access patterns, and user-defined tags, and on targeting non-genre categories for classification, such as mood labels and styles. This dissertation focused on investigating and developing effective data mining techniques for (1) organizing and annotating music data with styles, moods and user-assigned tags; (2) performing effective analysis of music data with features from diverse information sources; and (3) recommending music songs to the users utilizing both content features and user access patterns.

La numérisation 3D du patrimoine bâti est un procédé qui s’inscrit dans de multiples applications (documentation, visualisation, etc.), et peut tirer profit de la diversité des techniques de mesure disponibles. Afin d’améliorer la complétude et la qualité des livrables, de plus en plus de projets de numérisation s’appuient sur la combinaison de nuages de points provenant de différentes sources. La connaissance des performances propres aux différents capteurs, ainsi que de la qualité de leurs mesures, est alors souhaitable. Par la suite, plusieurs pistes peuvent être explorées en vue d’intégrer des nuages hétérogènes au sein d’un même projet, de leur recalage à la modélisation finale. Une approche pour le recalage simultané de plusieurs nuages de points est exposée dans ces travaux. La gestion de potentielles fautes parmi les observations, ou de bruit de mesure inhérent à certaines techniques de levé, est envisagée à travers l’ajout d’estimateurs robustes dans la méthodologie de recalage. / Three dimensional digitization of built heritage is involved in a wide range of applications (documentation, visualization, etc.), and may take advantage of the diversity of measurement techniques available. In order to improve the completeness as well as the quality of deliverables, more and more digitization projects rely on the combination of data coming from different sensors. To this end, the knowledge of sensor performances along with the quality of the measurements they produce is recommended. Then, different solutions can be investigated to integrate heterogeneous point clouds within a same project, from their registration to the modeling steps. A global approach for the simultaneous registration of multiple point clouds is proposed in this work, where the introduction of individual weights for each dataset is foreseen. Moreover, robust estimators are introduced in the registration framework, in order to deal with potential outliers or measurement noise among the data.

This thesis deals with design, implementation and testing of face recognition system processing video sequences captured by CCTV systems. The use of Local Binary Pattern Histograms (LPBH) and Nearest Neighbor (NN) classifier was suggested according to the survey of face recognition methods. Discrimination power of LBPH features was examined and individual informative features were searched based on Fisher discrimination ratio and mutual correlation. Cluster’s centorid method was utilized for pattern creation because of its best effect on system’s face recognition capability comparing several proposed methods. Software tool for effective face recognition system algorithms performance testing was developed. Video database IFaViD was assembled for training and performance testing of implemented face recognition system.

The purpose of this diploma thesis is award administrative building and evaluation of the most advantage variants of financial security on acquisition of real property. Part of thesis is the calculation of administrative price. At the end there are comments and comparision on selected products of mortgage marketplace.

Background: Empirical studies in psychiatric research and other fields often show substantially high refusal and drop-out rates. Non-participation and drop-out may introduce a bias whose magnitude depends on how strongly its determinants are related to the respective parameter of interest. Methods: When most information is missing, the standard approach is to estimate each respondent’s probability of participating and assign each respondent a weight that is inversely proportional to this probability. This paper contains a review of the major ideas and principles regarding the computation of statistical weights and the analysis of weighted data. Results: A short software review for weighted data is provided and the use of statistical weights is illustrated through data from the EDSP (Early Developmental Stages of Psychopathology) Study. The results show that disregarding different sampling and response probabilities can have a major impact on estimated odds ratios. Conclusions: The benefit of using statistical weights in reducing sampling bias should be balanced against increased variances in the weighted parameter estimates.

The empirical results from past research are quite clear. When the surrounding crime level goes up, housing prices go down. However, what has not been acknowledged in the previous literature is that different crimes might impact our willingness-to-pay heterogeneously. As most of the previous research is done through the usage of simple crime rates, this thesis acknowledges the relative severeness of different crimes. Using the newly developed crime harm index (CHI), the relative severity and harm inflicted by a specific crime is identified. The study is conducted in Sweden, Stockholm, using data for the year 2020. With the use of hedonic price equations, spatial models as well as graphical information system software, this thesis estimates a significant, and non-negligible negative relationship between increased area mean CHI and apartment prices. To the best of the author's knowledge, this is one of the very first analyses within the literature, which acknowledges the relative severeness of crimes, and the first to show a significant negative relationship between increased criminal harm and apartment prices. Further, the resulting estimates and method used in this thesis can be utilized to differentiate between the costs of different crimes, hence enabling precise cost estimates. These estimates could for example be of great use to policymaking, urban planners, and decision-making regarding safety investment.

A space camera is a promising candidate to address the non-stop rising interest for astrophysics research in the Compton regime. The MeVCube mission is intended to be launched in 2022, hosting an on-board Compton Camera. To better support the development of the instrument in this early stage, a series of feasibility studies to assess two potential launch orbits were performed. The studies were composed by a series of mission analysis simulations which permitted the characterisation of the orbital environments for the two orbital options. Several sources of background noise to the instrument were identified. The population of trapped protons and trapped electrons were simulated for the periods of Solar Minimum and Solar Maximum, as well as the levels of Galactic Cosmic Ray (GCR) flux. The performance of trade-off studies concluded that an equatorial orbit is more preferable for reducing the influence of background noise. To better estimate the environment effects at the equatorial orbit, the number of particles which can penetrate the detector shielding were simulated. The next step was to perform a series secondary studies whose aim were to simulate the induced current on the electrodes, produced by the interactions occurring within the detector. The actualisation of these simulations required the study of photon interaction with matter, the various Cadmium-Zink-Telluride (CZT) types and the how they operate, and the use of a sophisticated software to perform the appropriate simulations. COMSOL, which allows the method of FEA, was chosen as the tool to perform the simulations. The geometry of the detector voxel was primarily designed in SIEMENS NX. The geometry was inserted into COMSOL, where a number of iterations were performed to finalise the appropriate mesh size, which ensured an accurate representation of the Electric field and the Weighting potential within the detector voxel. The induced current on the electrodes was decided to be calculated via MATLAB. As a verification step it was thought useful to firstly plot the weighting potential of the three electrodes under test; the chosen anode pixel, the steering grid and the cathode. The process revealed a series of numerical errors, most likely introduced by the type of mesh chosen or by the data manipulation process via MATLAB. Significant reduction of the numerical errors would lead to more accurate values for the induced current. Unfortunately, due to time constraints this was a task that was not completed. Solving this problem would be optimal for future studies with MATLAB, as the induced current on the electrodes can be correctly calculated based on charge transport within the detector bulk. / MeVCube, DESY

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