35,230 research outputs found

    Path-tracing Monte Carlo Library for 3D Radiative Transfer in Highly Resolved Cloudy Atmospheres

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    Interactions between clouds and radiation are at the root of many difficulties in numerically predicting future weather and climate and in retrieving the state of the atmosphere from remote sensing observations. The large range of issues related to these interactions, and in particular to three-dimensional interactions, motivated the development of accurate radiative tools able to compute all types of radiative metrics, from monochromatic, local and directional observables, to integrated energetic quantities. In the continuity of this community effort, we propose here an open-source library for general use in Monte Carlo algorithms. This library is devoted to the acceleration of path-tracing in complex data, typically high-resolution large-domain grounds and clouds. The main algorithmic advances embedded in the library are those related to the construction and traversal of hierarchical grids accelerating the tracing of paths through heterogeneous fields in null-collision (maximum cross-section) algorithms. We show that with these hierarchical grids, the computing time is only weakly sensitivive to the refinement of the volumetric data. The library is tested with a rendering algorithm that produces synthetic images of cloud radiances. Two other examples are given as illustrations, that are respectively used to analyse the transmission of solar radiation under a cloud together with its sensitivity to an optical parameter, and to assess a parametrization of 3D radiative effects of clouds.Comment: Submitted to JAMES, revised and submitted again (this is v2

    Interactive context-aware user-driven metadata correction in digital libraries

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    Personal name variants are a common problem in digital libraries, reducing the precision of searches and complicating browsing-based interaction. The book-centric approach of name authority control has not scaled to match the growth and diversity of digital repositories. In this paper, we present a novel system for user-driven integration of name variants when interacting with web-based information-in particular digital library-systems. We approach these issues via a client-side JavaScript browser extension that can reorganize web content and also integrate remote data sources. Designed to be agnostic towards the web sites it is applied to, we illustrate the developed proof-of-concept system through worked examples using three different digital libraries. We discuss the extensibility of the approach in the context of other user-driven information systems and the growth of the Semantic Web

    Organising a daily visual diary using multifeature clustering

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    The SenseCam is a prototype device from Microsoft that facilitates automatic capture of images of a person's life by integrating a colour camera, storage media and multiple sensors into a small wearable device. However, efficient search methods are required to reduce the user's burden of sifting through the thousands of images that are captured per day. In this paper, we describe experiments using colour spatiogram and block-based cross-correlation image features in conjunction with accelerometer sensor readings to cluster a day's worth of data into meaningful events, allowing the user to quickly browse a day's captured images. Two different low-complexity algorithms are detailed and evaluated for SenseCam image clustering

    Resource selection and data fusion for multimedia international digital libraries: an overview of the MIND project

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    The inspiration for MIND grew out of the problems which users face when they have remote access to thousands of heterogeneous and distributed multimedia digital libraries. A user must know where to search, how to query different media, and how to combine information from diverse resources. As digital libraries continue to proliferate, in a variety of media and from a variety of sources, the problems of resource selection, query formulation and data fusion become major obstacles to effective search and retrieval. The key goal of MIND is to develop a common system for identifying, searching and combining results from multiple digital libraries. MIND, therefore, is investigating methods for resource description and selection (i.e., gathering and updating information about digital libraries to assist in selecting those which are most likely to contain the information sought), query processing (i.e. modifying the terms contained in a query and transforming the query into the local command language), data fusion (i.e., the merging of different data retrieved from different digital libraries) and information visualisation (in particular, the automatic generation of surrogates and presentation of fused retrieved data)

    Advanced content-based semantic scene analysis and information retrieval: the SCHEMA project

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    The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. Relevant research areas include: content-based multimedia analysis and automatic annotation of semantic multimedia content, combined textual and multimedia information retrieval, semantic -web, MPEG-7 and MPEG-21 standards, user interfaces and human factors. In this paper, recent advances in content-based analysis, indexing and retrieval of digital media within the SCHEMA Network are presented. These advances will be integrated in the SCHEMA module-based, expandable reference system

    A Revision Control System for Image Editing in Collaborative Multimedia Design

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    Revision control is a vital component in the collaborative development of artifacts such as software code and multimedia. While revision control has been widely deployed for text files, very few attempts to control the versioning of binary files can be found in the literature. This can be inconvenient for graphics applications that use a significant amount of binary data, such as images, videos, meshes, and animations. Existing strategies such as storing whole files for individual revisions or simple binary deltas, respectively consume significant storage and obscure semantic information. To overcome these limitations, in this paper we present a revision control system for digital images that stores revisions in form of graphs. Besides, being integrated with Git, our revision control system also facilitates artistic creation processes in common image editing and digital painting workflows. A preliminary user study demonstrates the usability of the proposed system.Comment: pp. 512-517 (6 pages
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