A Test-bed Facility for Research in Video Database Benchmarking

用于视频数据库基准测试研究的测试平台设施

• 批准号: 0209120
• 负责人: Walid Aref
• 金额: $ 13.5万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0209120&HistoricalAwards=false
• 关键词: Test; bed; Facility; Research; Video

This project will create a comprehensive test-bed facility to support research in video database management. Real-world video applications demand database technology that is capable of providing real-time content-based query and retrieval for stored digital video. However, video is a complex data type that requires a significant amount of preprocessing for content representation before research issues in database management for real-time video data can be addressed. This project will facilitate video database research by abstracting video as a fundamental and fully functional database data type. Tools for video content analysis, feature extraction and high-dimensional indexing will be integrated into the test-bed facility, which will then be used to address several research challenges in the management of real-time streamed video data, including multi-feature nearest neighbor queries, feature-based query processing, video operators, buffer management for streaming video, and continuous video streaming with real-time constraints. The system will provide standardized methods for integrating components and measuring their performance, and will be furnished with a large collection of indexed videos. The underlying database management system, video-processing tools, and video data will form a complete environment for the video database research community, providing an effective platform for implementation, validation and evaluation of new video database technology.

该项目将创建一个综合试验台设施，以支持视频数据库管理的研究。现实世界的视频应用需要能够为存储的数字视频提供基于内容的实时查询和检索的数据库技术。然而，视频是一个复杂的数据类型，需要大量的内容表示的预处理之前，在数据库管理的实时视频数据的研究问题可以得到解决。这个项目将促进视频数据库的研究，抽象视频作为一个基本的和功能齐全的数据库数据类型。用于视频内容分析、特征提取和高维索引的工具将被集成到测试台设施中，然后将用于解决实时流视频数据管理中的若干研究挑战，包括多特征最近邻查询、基于特征的查询处理、视频运算符、流视频的缓冲区管理以及具有实时约束的连续视频流。该系统将提供标准化的方法，用于整合各组成部分和衡量其性能，并将提供大量索引录像。底层的数据库管理系统、视频处理工具和视频数据将为视频数据库研究社区形成一个完整的环境，为新的视频数据库技术的实施、验证和评估提供一个有效的平台。