DREAM: Dynamic RetriEval, Analysis and semantic metadata Management (DREAM)

DREAM：动态检索、分析和语义元数据管理 (DREAM)

• 批准号: DT/E006140/1
• 负责人: Atta Badii
• 金额: $ 56.25万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2006
• 资助国家: 英国
• 起止时间: 2006 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=DT%2FE006140%2F1
• 关键词: DREAM; Dynamic; RetriEval; Analysis; semantic

DREAM will develop efficient storage, management, indexing, search, use and re-use of digital media assets for the postproduction industry. The R&D focuses on the creation and use of metadata generated from low-level content analysis and high-level semantic awareness, and the incorporation of semantic metadata into the workflow process. A novel Metadatabase and semantic intervention will support data analysis, indexing and retrieval. DREAM will create media industry products in the mid-term, and enable the subsequent development of applications in other sectors including security, medical, corporate, and consumer. The project is led by award-winning UK postproduction technology developer FilmLight, working with a company specialising in media software plug-ins (The Foundry), a major user partner (Double Negative) and a university partner (University of Reading IMSS) specialising in semantic technologies. There are three technical strands. The first will define the semantic infrastructure, involving metadata design and domain ontologies and develop tools for semantic video indexing, query formulation and retrieval. In this we will address the 'semantic gap' by combining metadata extracted by image processing with semantic descriptions derived from a network of ontologies, behavioural models and interactive techniques that recognise user behaviour and context. Where automatic detection from low-level processes gives insufficient clues, iterative cycles of image processing may be interleaved with feature extraction and semantic labelling until there is resolution. The second strand will develop new algorithms and tools to extract very rich, persistent metadata based on image processing and motion analysis. The image analysis will be linked to semantic knowledge to improve the accuracy of metadata extraction, and the resulting metadata will in turn improve the object recognition for information retrieval (by for example producing much more accurate human maps than previously possible). The third strand addresses the database level and data management, associating the metadata and data as they move through the system. In an image-based data world, such as digital cinema, the objects are too large and numerous to hold in a database. DREAM will create a Metadatabase to track the metadata associated with files held in any kind of distributed file system. The Metadatabase may be both physical and virtual, since some of the metadata types (motion vector analysis and derivatives) are large files that may be stored in the file system itself. The resulting system may be based on a single site or on multiple sites connected by a secure VPN. The project will result in new scientific and technological knowledge that forms the basis for a range of media industry products in the mid-term, and for further R&D leading to their long-term application to other sectors. The principal deliverables will be: - Ontologies and semantic models of postproduction processes, domain specific models relating to genres (such as action, drama) and objects appearing in them - A semantic resolution engine for labelling and query support - Smart proxy enabled tools for detection, labelling and transcoding data - Templates and role-specific interfaces for semi-automatic semantic labelling, query and retrieval - Algorithms for metadata extraction from low-level features of moving images, with semantic links to higher-level features - Metadata format definitions and interface for the OFX plug-in standard - New tools and plug-ins for motion estimation, object and character matting, feature extraction and modification based on the use of persistent metadata and semantic analysis - A metadatabase linked to a semantically enabled data management application for very large distributed file systems - An integrated prototype solution combining semantic retrieval tools, image analysis and metadata extraction, metadatabase and data management system

DREAM将为后期制作行业开发高效的数字媒体资产存储、管理、索引、搜索、使用和再利用。研发重点是创建和使用由低级内容分析和高级语义感知生成的元数据，并将语义元数据整合到工作流过程中。一个新的元数据库和语义干预将支持数据分析、索引和检索。DREAM将在中期开发媒体行业产品，并在安全、医疗、企业和消费等其他领域开发应用。该项目由屡获殊荣的英国后期技术开发商FilmLight领导，与一家专门从事媒体软件插件的公司（The Foundry）、一家主要用户合作伙伴（Double Negative）和一家专门从事语义技术的大学合作伙伴（雷丁大学IMSS）合作。有三个技术方面。第一部分将定义语义基础结构，包括元数据设计和领域本体，并开发用于语义视频索引、查询公式和检索的工具。在本文中，我们将通过将图像处理提取的元数据与来自本体网络、行为模型和识别用户行为和上下文的交互技术的语义描述相结合来解决“语义差距”。当低级过程的自动检测不能提供足够的线索时，图像处理的迭代循环可能与特征提取和语义标记交织在一起，直到有解决方案。第二部分将开发新的算法和工具，以提取基于图像处理和运动分析的非常丰富、持久的元数据。图像分析将与语义知识联系起来，以提高元数据提取的准确性，所得到的元数据将反过来提高信息检索的对象识别（例如，通过生成比以前更准确的人类地图）。第三部分涉及数据库级别和数据管理，在元数据和数据在系统中移动时将它们关联起来。在基于图像的数据世界中，例如数字电影，对象太大且数量太多，无法保存在数据库中。DREAM将创建一个元数据库来跟踪与任何类型的分布式文件系统中保存的文件相关的元数据。元数据库可以是物理的也可以是虚拟的，因为一些元数据类型（运动矢量分析和衍生）是可以存储在文件系统本身中的大文件。生成的系统可以基于单个站点，也可以基于通过安全VPN连接的多个站点。该项目将产生新的科学和技术知识，这些知识将在中期形成一系列媒体行业产品的基础，并为进一步的研发提供基础，从而将其长期应用于其他领域。主要的交付成果将是：-后期制作过程的本体和语义模型，与类型（如动作、戏剧）和其中出现的对象相关的领域特定模型-用于标记和查询支持的语义解析引擎-用于检测、标记和转码数据的智能代理启用工具-用于半自动语义标记、查询和检索的模板和角色特定接口-用于从运动图像的低级特征中提取元数据的算法与高级功能的语义链接-元数据格式定义和OFX插件标准的接口-基于持久元数据和语义分析的使用，用于运动估计、对象和字符消光、特征提取和修改的新工具和插件-与大型分布式文件系统的语义启用数据管理应用程序链接的元数据库-结合语义检索工具的集成原型解决方案。图像分析和元数据提取，元数据库和数据管理系统

项目成果

Scaling Topic Maps

缩放主题图

• DOI: 10.1007/978-3-540-70874-2_21
• 发表时间: 2008
• 作者: Badii A