US-Singapore Workshop: Collaborative Research: Understand the World by Analyzing Many Video Streams

美国-新加坡研讨会：合作研究：通过分析许多视频流了解世界

• 批准号: 1427688
• 负责人: Ketan Mayer-Patel
• 金额: $ 0.91万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-12-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1427688&HistoricalAwards=false
• 关键词: US; Singapore; Workshop; Collaborative; Research

NSF CNIC US-Singapore Workshop: Collaborative Research: Understand the World by Analyzing Many Video Streams Many thousands of network cameras provide near real-time view of the world. Valuable scientific information could be extracted by analyzing the large amounts of data. However, most of the data are never analyzed or archived. Analysis programs must be able to retrieve data from distributed sources, manage network accesses, schedule computation resources, allocate storage space, analyze the data, store the results, and present the results in formats that are easy to comprehend. Although the data are available, analyses today are limited due to the lack of a software framework to write and execute computer programs. To harvest the knowledge from the data, the researchers from six universities are creating a system that can analyze the vast amount of visual data. The team will organize a workshop in December 2014 in Singapore. In this workshop, the team will share the information of the projects currently been conducted independently in the six universities. The researchers will present and demonstrate their projects, discuss and develop a plan for collaboration. The team includes Yung-Hsiang Lu (lead, Purdue University), Ketan Mayer-Patel (University of North Carolina), Cong Liu (University of Texas Dallas), Wei Tsang Ooi (National University of Singapore), Jason Gu (Singapore University of Technology and Design), Yonggang Wen (Nanyang Technological University).

NSF CNIC美国-新加坡研讨会：合作研究：通过分析许多视频流了解世界成千上万的网络摄像机提供近乎实时的世界视图。通过对大量数据的分析，可以提取出有价值的科学信息。然而，大多数数据从未被分析或存档。分析程序必须能够从分布式数据源检索数据，管理网络访问，调度计算资源，分配存储空间，分析数据，存储结果，并以易于理解的格式呈现结果。虽然数据是可用的，但由于缺乏编写和执行计算机程序的软件框架，今天的分析是有限的。为了从数据中获取知识，来自六所大学的研究人员正在创建一个可以分析大量视觉数据的系统。该小组将于2014年12月在新加坡举办一次研讨会。在这次研讨会上，该团队将分享目前在六所大学独立开展的项目的信息。研究人员将展示他们的项目，讨论和制定合作计划。该团队包括Yung-Hsiang Lu（领导，普渡大学），Ketan Mayer-Patel（北卡罗来纳州大学），Cong Liu（德克萨斯大学达拉斯），Wei Tsang Ooi（新加坡国立大学），Jason Gu（新加坡科技设计大学），Yonggang Wen（南洋理工大学）。