56,652 research outputs found

    The hunt for submarines in classical art: mappings between scientific invention and artistic interpretation

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    This is a report to the AHRC's ICT in Arts and Humanities Research Programme. This report stems from a project which aimed to produce a series of mappings between advanced imaging information and communications technologies (ICT) and needs within visual arts research. A secondary aim was to demonstrate the feasibility of a structured approach to establishing such mappings. The project was carried out over 2006, from January to December, by the visual arts centre of the Arts and Humanities Data Service (AHDS Visual Arts).1 It was funded by the Arts and Humanities Research Council (AHRC) as one of the Strategy Projects run under the aegis of its ICT in Arts and Humanities Research programme. The programme, which runs from October 2003 until September 2008, aims ‘to develop, promote and monitor the AHRC’s ICT strategy, and to build capacity nation-wide in the use of ICT for arts and humanities research’.2 As part of this, the Strategy Projects were intended to contribute to the programme in two ways: knowledge-gathering projects would inform the programme’s Fundamental Strategic Review of ICT, conducted for the AHRC in the second half of 2006, focusing ‘on critical strategic issues such as e-science and peer-review of digital resources’. Resource-development projects would ‘build tools and resources of broad relevance across the range of the AHRC’s academic subject disciplines’.3 This project fell into the knowledge-gathering strand. The project ran under the leadership of Dr Mike Pringle, Director, AHDS Visual Arts, and the day-to-day management of Polly Christie, Projects Manager, AHDS Visual Arts. The research was carried out by Dr Rupert Shepherd

    Digital Image Access & Retrieval

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    The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

    Recent Developments in Cultural Heritage Image Databases: Directions for User-Centered Design

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    published or submitted for publicatio

    Slovenian Virtual Gallery on the Internet

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    The Slovenian Virtual Gallery (SVG) is a World Wide Web based multimedia collection of pictures, text, clickable-maps and video clips presenting Slovenian fine art from the gothic period up to the present days. Part of SVG is a virtual gallery space where pictures hang on the walls while another part is devoted to current exhibitions of selected Slovenian art galleries. The first version of this application was developed in the first half of 1995. It was based on a file system for storing all the data and custom developed software for search, automatic generation of HTML documents, scaling of pictures and remote management of the system. Due to the fast development of Web related tools a new version of SVG was developed in 1997 based on object-oriented relational database server technology. Both implementations are presented and compared in this article with issues related to the transion between the two versions. At the end, we will also discuss some extensions to SVG. We will present the GUI (Graphical User Interface) developed specially for presentation of current exhibitions over the Web which is based on GlobalView panoramic navigation extension to developed Internet Video Server (IVS). And since SVG operates with a lot of image data, we will confront with the problem of Image Content Retrieval

    CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

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    Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

    Index to Library Trends Volume 38

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    published or submitted for publicatio

    Hierarchical Attention Network for Visually-aware Food Recommendation

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    Food recommender systems play an important role in assisting users to identify the desired food to eat. Deciding what food to eat is a complex and multi-faceted process, which is influenced by many factors such as the ingredients, appearance of the recipe, the user's personal preference on food, and various contexts like what had been eaten in the past meals. In this work, we formulate the food recommendation problem as predicting user preference on recipes based on three key factors that determine a user's choice on food, namely, 1) the user's (and other users') history; 2) the ingredients of a recipe; and 3) the descriptive image of a recipe. To address this challenging problem, we develop a dedicated neural network based solution Hierarchical Attention based Food Recommendation (HAFR) which is capable of: 1) capturing the collaborative filtering effect like what similar users tend to eat; 2) inferring a user's preference at the ingredient level; and 3) learning user preference from the recipe's visual images. To evaluate our proposed method, we construct a large-scale dataset consisting of millions of ratings from AllRecipes.com. Extensive experiments show that our method outperforms several competing recommender solutions like Factorization Machine and Visual Bayesian Personalized Ranking with an average improvement of 12%, offering promising results in predicting user preference for food. Codes and dataset will be released upon acceptance

    Metadata Augmentation for Semantic- and Context- Based Retrieval of Digital Cultural Objects

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    Cultural objects are increasingly stored and generated in digital form, yet effective methods for their indexing and retrieval still remain an open area of research. The main problem arises from the disconnection between the content-based indexing approach used by computer scientists and the description-based approach used by information scientists. There is also a lack of representational schemes that allow the alignment of the semantics and context with keywords and low-level features that can be automatically extracted from the content of these cultural objects. This paper presents an integrated approach to address these problems, taking advantage of both computer science and information science approaches. The focus is on the rationale and conceptual design of the system and its various components. In particular, we discuss techniques for augmenting commonly used metadata with visual features and domain knowledge to generate high-level abstract metadata which in turn can be used for semantic and context-based indexing and retrieval. We use a sample collection of Vietnamese traditional woodcuts to demonstrate the usefulness of this approach
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