Extending the 5S Framework of Digital Libraries to support Complex Objects, Superimposed Information, and Content-Based Image Retrieval Services

Advanced services in digital libraries (DLs) have been developed and widely used to address the required capabilities of an assortment of systems as DLs expand into diverse application domains. These systems may require support for images (e.g., Content-Based Image Retrieval), Complex (information) Objects, and use of content at fine grain (e.g., Superimposed Information). Due to the lack of consensus on precise theoretical definitions for those services, implementation efforts often involve ad hoc development, leading to duplication and interoperability problems. This article presents a methodology to address those problems by extending a precisely specified minimal digital library (in the 5S framework) with formal definitions of aforementioned services. The theoretical extensions of digital library functionality presented here are reinforced with practical case studies as well as scenarios for the individual and integrative use of services to balance theory and practice. This methodology has implications that other advanced services can be continuously integrated into our current extended framework whenever they are identified. The theoretical definitions and case study we present may impact future development efforts and a wide range of digital library researchers, designers, and developers

Fine-Grained Image Analysis with Deep Learning: A Survey

Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer vision and pattern recognition, and underpins a diverse set of real-world applications. The task of FGIA targets analyzing visual objects from subordinate categories, e.g., species of birds or models of cars. The small inter-class and large intra-class variation inherent to fine-grained image analysis makes it a challenging problem. Capitalizing on advances in deep learning, in recent years we have witnessed remarkable progress in deep learning powered FGIA. In this paper we present a systematic survey of these advances, where we attempt to re-define and broaden the field of FGIA by consolidating two fundamental fine-grained research areas -- fine-grained image recognition and fine-grained image retrieval. In addition, we also review other key issues of FGIA, such as publicly available benchmark datasets and related domain-specific applications. We conclude by highlighting several research directions and open problems which need further exploration from the community.Comment: Accepted by IEEE TPAM

Audiovisual and Chill: An Evaluation of Video Digital Libraries and Catalogues

Research Problem: This research investigates how well video digital libraries and catalogues used in academic libraries meet user expectations. This is in the context of increasing use and demand for online audiovisual content by the wider community, as well as growing use of audiovisual materials for teaching, learning, and research at academic institutions. It also aims to give an understanding of how well libraries are meeting the challenges of delivering audiovisual materials to users in an on-demand world. Methodology: Twelve platforms—developed between 1996 and 2015—are evaluated against 23 user-centred criteria, divided into four core areas: retrieval functionality, user interface, collection qualities, and user support. Results: The study found that not one of the platforms evaluated met all the evaluation criteria, and identified three key areas in the usability of the video digital libraries and catalogues: search and retrieval, technology, and structure, scope, and strategy. Implications: From this we gain an understanding of performance and usability of video digital libraries and catalogues currently in use by academic libraries. We also learn about the difficulties those working with audiovisual materials are facing, and also of the solutions that are being proposed. Findings of this study could help influence decision making, development of future platforms, and influence policies for delivering audiovisual materials to users

Behavioural disinhibition in the syndromes associated with frontotemporal lobar degeneration

The different clinical syndromes caused by frontotemporal lobar degeneration (FTLD) have highly heterogenous and overlapping features which complicate clinical and research practice. Behavioural impairments are associated with all FTLD syndromes, cause high morbidity and lack proven symptomatic treatments. Treatments for cognitive and behavioural impairment in other neurodegenerative diseases include restoration of neurotransmitter deficits. Deficits in the neurotransmitters glutamate and GABA occur in FTLD syndromes and are associated with behavioural disinhibition in other diseases. I propose that these neurotransmitter deficits contribute to behavioural change in FTLD syndromes. This thesis has two main aims. First, to develop a transdiagnostic approach to FTLD syndromes to facilitate a better understanding of aetiology, pathophysiology and in due course their symptomatic treatment. Second, to use this approach to test the hypothesis that glutamate and GABA deficits are associated with behavioural disinhibition in FTLD syndromes. In a cross-sectional epidemiological study, I examined 310 of 365 regional patients with a FTLD-associated syndrome, including behavioural variant frontotemporal dementia, the nonfluent and semantic variants of primary progressive aphasia, progressive supranuclear palsy and corticobasal syndrome. Multivariate analyses of clinical features and brain morphometry identified components that showed considerable overlap across the diagnostic groups. The transdiagnostic components of clinical features predicted neuropathology better than the current FTLD diagnostic labels. Behavioural disturbance, including disinhibition, was associated with reduced functionally independent survival, irrespective of diagnosis. Next, I investigated the role of glutamate and GABA in behavioural disinhibition. Ultrahigh-field magnetic resonance spectroscopy was used to measure glutamate and GABA in the frontal cortex of 44 patients with a FTLD syndrome and 20 healthy controls. Bayesian modelling of a response inhibition task was used to quantify behavioural disinhibition. Both neurotransmitters were reduced in the frontal cortex, but not occipital cortex, of patients compared to controls. Glutamate and GABA concentrations in the frontal cortex were inversely associated with behavioural disinhibition. In summary, the transdiagnostic approach provided new insights into the phenotypic heterogeneity in FTLD syndromes. Behavioural disinhibition, which can occur to a variable degree in all FTLD syndromes, was associated with reduced functionally independent survival. GABA and glutamate deficits in the frontal cortex are associated with behavioural disinhibition and are a potential target for future treatments.Holt Fellowshi

Image registration: Features and applications

Ph.DDOCTOR OF PHILOSOPH

Browse-to-search

This demonstration presents a novel interactive online shopping application based on visual search technologies. When users want to buy something on a shopping site, they usually have the requirement of looking for related information from other web sites. Therefore users need to switch between the web page being browsed and other websites that provide search results. The proposed application enables users to naturally search products of interest when they browse a web page, and make their even causal purchase intent easily satisfied. The interactive shopping experience is characterized by: 1) in session - it allows users to specify the purchase intent in the browsing session, instead of leaving the current page and navigating to other websites; 2) in context - -the browsed web page provides implicit context information which helps infer user purchase preferences; 3) in focus - users easily specify their search interest using gesture on touch devices and do not need to formulate queries in search box; 4) natural-gesture inputs and visual-based search provides users a natural shopping experience. The system is evaluated against a data set consisting of several millions commercial product images. © 2012 Authors

Segmentation and Deformable Modelling Techniques for a Virtual Reality Surgical Simulator in Hepatic Oncology

Liver surgical resection is one of the most frequently used curative therapies. However, resectability is problematic. There is a need for a computer-assisted surgical planning and simulation system which can accurately and efficiently simulate the liver, vessels and tumours in actual patients. The present project describes the development of these core segmentation and deformable modelling techniques. For precise detection of irregularly shaped areas with indistinct boundaries, the segmentation incorporated active contours - gradient vector flow (GVF) snakes and level sets. To improve efficiency, a chessboard distance transform was used to replace part of the GVF effort. To automatically initialize the liver volume detection process, a rotating template was introduced to locate the starting slice. For shape maintenance during the segmentation process, a simplified object shape learning step was introduced to avoid occasional significant errors. Skeletonization with fuzzy connectedness was used for vessel segmentation. To achieve real-time interactivity, the deformation regime of this system was based on a single-organ mass-spring system (MSS), which introduced an on-the-fly local mesh refinement to raise the deformation accuracy and the mesh control quality. This method was now extended to a multiple soft-tissue constraint system, by supplementing it with an adaptive constraint mesh generation. A mesh quality measure was tailored based on a wide comparison of classic measures. Adjustable feature and parameter settings were thus provided, to make tissues of interest distinct from adjacent structures, keeping the mesh suitable for on-line topological transformation and deformation. More than 20 actual patient CT and 2 magnetic resonance imaging (MRI) liver datasets were tested to evaluate the performance of the segmentation method. Instrument manipulations of probing, grasping, and simple cutting were successfully simulated on deformable constraint liver tissue models. This project was implemented in conjunction with the Division of Surgery, Hammersmith Hospital, London; the preliminary reality effect was judged satisfactory by the consultant hepatic surgeon

Countervisuality as Policy Feedback: A Critical Policy Study on the Symbolic Role of Visual Culture in Contemporary Antiracist Resistance

This critical interpretive study explores the relationship between public policy and visual culture. Drawing from five areas of research literature on (1) policy feedback theory, (2) the spectacle, (3) art and visual culture, (4) Black feminist theory, (5) and critical philosophies of resistance, images of contemporary antiracist activism are conceptualized as a form of policy feedback. Photographs of Ieshia Evans, Bree Newsome, and a self-portrait by Nona Faustine are reverse searched through Google Images. Utilizing constructivist grounded theory, a collection of publicly available news articles, blogs, and social media content are analyzed to better understand how mass publics engage with these images online. The findings reveal that a unique form of social learning takes place as publics orient themselves to the images in terms of lived experience, current events, and history; as they make sense of images by connecting novel information to previously learned information; and, as they apply the images in a variety of ways in civil society, politics, and market. This form of extra-institutional learning appears to be consistent with current literature on public pedagogy. Implications for the field of public policy are discussed