Searching for repeated video sequences

In this paper, we propose a new method to search different instances of a video sequence inside a long video and/or video collection. The proposed method is robust to view point and illumination changes which may occur since the sequences are captured in different times with different cameras, and to the differences in the order and the number of frames in the sequences which may occur due to editing. The algorithm does not require any query to be given for searching, and finds all repeating video sequences inside a long video in a fully automatic way. First, the frames in a video are ranked according to their similarity on the distribution of salient points and colour values. Then, a tree based approach is used to seek for the repetitions of a video sequence if there is any. Results are provided on a full length feature movie, Run Lola Run and on commercials of TRECVID 2004 news video corpus. Copyright 2007 ACM

Detection and tracking of repeated sequences in videos

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2007.Thesis (Master's) -- Bilkent University, 2007.Includes bibliographical references leaves 87-92.In this thesis, we propose a new method to search different instances of a video sequence inside a long video. The proposed method is robust to view point and illumination changes which may occur since the sequences are captured in different times with different cameras, and to the differences in the order and the number of frames in the sequences which may occur due to editing. The algorithm does not require any query to be given for searching, and finds all repeating video sequences inside a long video in a fully automatic way. First, the frames in a video are ranked according to their similarity on the distribution of salient points and colour values. Then, a tree based approach is used to seek for the repetitions of a video sequence if there is any. These repeating sequences are pruned for more accurate results in the last step. Results are provided on two full length feature movies, Run Lola Run and Groundhog Day, on commercials of TRECVID 2004 news video corpus and on dataset created for CIVR Copy Detection Showcase 2007. In these experiments, we obtain %93 precision values for CIVR2007 Copy Detection Showcase dataset and exceed %80 precision values for other sets.Can, TolgaM.S

3D forensic crime scene reconstruction involving immersive technology: A systematic literature review

Recreation of 3D crime scenes is critical for law enforcement in the investigation of serious crimes for criminal justice responses. This work presents a premier systematic literature review (SLR) that offers a structured, methodical, and rigorous approach to understanding the trend of research in 3D crime scene reconstruction as well as tools, technologies, methods, and techniques employed thereof in the last 17 years. Major credible scholarly database sources, Scopus, and Google Scholar, which index journals and conferences that are promoted by entities such as IEEE, ACM, Elsevier, and SpringerLink were explored as data sources. Of the initial 17, 912 papers that resulted from the first search string, 258 were found to be relevant to our research questions after implementing the inclusion and exclusion criteria

Semantic interpretation of events in lifelogging

The topic of this thesis is lifelogging, the automatic, passive recording of a person’s daily activities and in particular, on performing a semantic analysis and enrichment of lifelogged data. Our work centers on visual lifelogged data, such as taken from wearable cameras. Such wearable cameras generate an archive of a person’s day taken from a first-person viewpoint but one of the problems with this is the sheer volume of information that can be generated. In order to make this potentially very large volume of information more manageable, our analysis of this data is based on segmenting each day’s lifelog data into discrete and non-overlapping events corresponding to activities in the wearer’s day. To manage lifelog data at an event level, we define a set of concepts using an ontology which is appropriate to the wearer, applying automatic detection of concepts to these events and then semantically enriching each of the detected lifelog events making them an index into the events. Once this enrichment is complete we can use the lifelog to support semantic search for everyday media management, as a memory aid, or as part of medical analysis on the activities of daily living (ADL), and so on. In the thesis, we address the problem of how to select the concepts to be used for indexing events and we propose a semantic, density- based algorithm to cope with concept selection issues for lifelogging. We then apply activity detection to classify everyday activities by employing the selected concepts as high-level semantic features. Finally, the activity is modeled by multi-context representations and enriched by Semantic Web technologies. The thesis includes an experimental evaluation using real data from users and shows the performance of our algorithms in capturing the semantics of everyday concepts and their efficacy in activity recognition and semantic enrichment

Efficient Bayesian methods for clustering.

One of the most important goals of unsupervised learning is to discover meaningful clusters in data. Clustering algorithms strive to discover groups, or clusters, of data points which belong together because they are in some way similar. The research presented in this thesis focuses on using Bayesian statistical techniques to cluster data. We take a model-based Bayesian approach to defining a cluster, and evaluate cluster membership in this paradigm. Due to the fact that large data sets are increasingly common in practice, our aim is for the methods in this thesis to be efficient while still retaining the desirable properties which result from a Bayesian paradigm. We develop a Bayesian Hierarchical Clustering (BHC) algorithm which efficiently addresses many of the drawbacks of traditional hierarchical clustering algorithms. The goal of BHC is to construct a hierarchical representation of the data, incorporating both finer to coarser grained clusters, in such a way that we can also make predictions about new data points, compare different hierarchies in a principled manner, and automatically discover interesting levels of the hierarchy to examine. BHC can also be viewed as a fast way of performing approximate inference in a Dirichlet Process Mixture model (DPM), one of the cornerstones of nonparametric Bayesian Statistics. We create a new framework for retrieving desired information from large data collections, Bayesian Sets, using Bayesian clustering techniques. Unlike current retrieval methods, Bayesian Sets provides a principled framework which leverages the rich and subtle information provided by queries in the form of a set of examples. Whereas most clustering algorithms are completely unsupervised, here the query provides supervised hints or constraints as to the membership of a particular cluster. We call this "clustering on demand", since it involves forming a cluster once some elements of that cluster have been revealed. We use Bayesian Sets to develop a content-based image retrieval system. We also extend Bayesian Sets to a discriminative setting and use this to perform automated analogical reasoning. Lastly, we develop extensions of clustering in order to model data with more complex structure than that for which traditional clustering is intended. Clustering models traditionally assume that each data point belongs to one and only one cluster, and although they have proven to be a very powerful class of models, this basic assumption is somewhat limiting. For example, there may be overlapping regions where data points actually belong to multiple clusters, like movies which can each belong to multiple genres. We extend traditional mixture models to create a statistical model for overlapping clustering, the Infinite Overlapping Mixture Model (IOMM), in a non-parametric Bayesian setting, using the Indian Buffet Process (IBP). We also develop a Bayesian Partial Membership model (BPM), which allows data points to have partial membership in multiple clusters via a continuous relaxation of a finite mixture model

Recuperação de informação multimédia em memórias pessoais

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaEsta dissertação descreve soluções para a recuperação e anotação de informação multimédia em memórias pessoais. Estas propostas incluem métodos de recuperação e anotação de fotografias,baseados na extracção de informação semântica em imagens, e aplicações de recuperação e anotação em três cenários diferentes: ambientes domésticos, cenários móveis e em actividades de entretenimento. Os métodos propostos para recuperar e anotar fotos utilizam informação multimodal, nomeadamente,características visuais, informação de áudio e metadados contextuais obtidos no instante de captura. Esta metodologia baseia-se na análise semântica de imagens, obtida utilizando estes dados, para recuperar e anotar imagens automaticamente. Os metadados contextuais utilizados são o instante de captura da foto e a sua localização geográfica. Para ambientes domésticos, é proposta uma aplicação para partilha de momentos relevantes do passado baseada na pesquisa e visualização de fotos pessoais. A interface inclui uma linguagem visual baseada em ícones para definir a pesquisa e permite interrogar a colecção pessoal com objectos físicos. Para cenários móveis, nomeadamente em actividades turísticas, é descrita uma aplicação para partilha de fotos no momento da visita a locais de interesse, por exemplo, museus ou lugares históricos. A partilha de imagens é baseada no método de recuperação proposto. A aplicação permite a captura de fotografias e a sua anotação com informação de áudio obtida segundos após a captura e com coordenadas de localização geográfica obtidas pelo receptor GPS (Global Positioning System) incluído. Para corrigir erros produzidos pelo método automático de recuperação e anotação é proposta uma aplicação para anotação semiautomática de imagens. Esta aplicação inclui um jogo de computador para anotar imagens baseado numa interface gestual de modo a motivar os utilizadores para a tarefa da anotação. A tese apresenta as soluções referidas descrevendo a metodologia de concepção utilizada no desenvolvimento das aplicações, incluindo os resultados obtidos nos testes de usabilidade efectuados. São também apresentados e discutidos resultados da avaliação efectuada para validar os métodos de recuperação e anotação em cada uma das aplicações

Modellgetriebene Entwicklung inhaltsbasierter Bildretrieval-Systeme auf der Basis von objektrelationalen Datenbank-Management-Systeme

In this thesis, the model-driven software development paradigm is employed in order to support the development of Content-based Image Retrieval Systems (CBIRS) for different application domains. Modeling techniques, based on an adaptable conceptual framework model, are proposed for deriving the components of a concrete CBIRS. Transformation techniques are defined to automatically implement the derived application specific models in an object-relational database management system. A set of criteria assuring the quality of the transformation are derived from the theory for preserving information capacity applied in database design.In dieser Dissertation wird das Paradigma des modellgetriebenen Softwareentwurfs für die Erstellung von inhaltsbasierten Bildretrieval-Systemen verwendet. Ein adaptierbares Frameworkmodell wird für die Ableitung des Modells eines konkreten Bildretrieval-Systems eingesetzt. Transformationstechniken für die automatische Generierung von Implementierungen in Objektorientierten Datenbank-Management-Systemen aus dem konzeptuellen Modell werden erarbeitet. Die aus der Theorie des Datenbankentwurfs bekannten Anforderungen zur Kapazitätserhaltung der Transformation werden verwendet, um Kriterien für die erforderliche Qualität der Transformation zu definieren

Cognitive aging in people living with HIV: concept development and empirical evidence from several longitudinal cohorts in Australia and beyond

With widespread access to combination anti-retroviral therapy (cART) and HIV suppression, life expectancy among people living with HIV (PLHIV) is increasing more than ever. According to UNAIDS, there were 8.1 million older PLHIV (i.e., 50 years of age and over) in 2020 globally. Although HIV-associated dementia has become rare in the cART era, mild neurocognitive impairments remain prevalent among PLHIV (~30% in virally suppressed). With aging, there is an increasing concern that HIV may precipitate neurocognitive abnormal aging because HIV is associated with increased markers of aging (e.g., immunosenescence and hyper-coagulopathy) and multiple age and HIV-related comorbidities (e.g., cardiovascular diseases). Importantly, these comorbidities occur at an earlier age and at a higher rate among PLHIV compared to age-matched HIV-negative persons. Earlier, more severe and more rapidly progressing neurocognitive impairment would have major public health consequences for the millions of PLHIV and the healthcare system. The overarching aim of this PhD thesis is to determine whether having chronic stable HIV infection and suppressive ART is associated with abnormal cognitive aging including premature cognitive aging (HIV and age synergistically/addictively lead to much lower cognitive performance at a younger age compared to controls), accentuated cognitive aging (HIV and age synergistically/addictively lead to much greater prevalence and severity of neurocognitive impairment), and/or accelerated cognitive aging (HIV and age synergistically/ addictively lead to much more rapid progression of neurocognitive impairment). To address these questions, we used a range of scientific methodologies including a systematic review, and several types of advanced statistical analyses using national and international longitudinal cohort data. First, to contextualise the potential public health consequences of cognitive aging in PLHIV, we conducted a narrative review of the burden of established dementia risk factors among PLHIV. We identified that the burden of several major dementia risk factors is much greater among PLHIV than in the general population. Second, we conducted the first-ever systematic review evaluating the current evidence for premature, accentuated and accelerated cognitive aging among PLHIV. We determined moderate evidence for premature cognitive aging and strong evidence for accelerated cognitive aging, while accentuated cognitive aging had not been optimally assessed. Lastly, addressing the previous literature major limitations (low sample size, cross-sectional study design, low proportion of older PLHIV, and inadequate controls/norms), we quantified the profiles of cognitive aging in four longitudinal studies of PLHIV. We demonstrated robust trends for premature cognitive aging among PLHIV compared to age-matched HIV-negative persons. We also demonstrated that older PLHIV had a higher risk for both neurocognitive impairment and neurocognitive decline compared to younger PLHIV, while controlling for normative age effect. These results are indicative of both accentuated and accelerated aging, although our research identified the need for longer-term studies using very large sample size to assess these trends especially in PLHIV older than 70+. Based on these findings, we discussed implications for clinical practice and future research directions

Health beliefs and behaviour of a population screened for chronic kidney disease in Sarawak: a mixed methods study

This thesis had two objectives: to determine the socio-demographic, metabolic determinants and prevalence of chronic kidney disease (CKD) and metabolic syndrome (MetS) in Sarawak; to link these findings to health-related beliefs and behaviours in this population. We conducted a mixed-methods sequential design where 270 cases-controls were quantitatively studied and a purposefully selected subset of 32, were studied through qualitative interviews. The thesis discusses how health related beliefs/ behaviours influence the development of MetS and CKD