Human Activity Scripts and Queries for Video Databases

视频数据库的人类活动脚本和查询

• 批准号: 0208300
• 负责人: Jezekiel Ben-Arie
• 金额: $ 18万
• 依托单位: University of Illinois at Chicago
• 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=0208300&HistoricalAwards=false
• 关键词: Human; Activity; Scripts; Queries; Video

This project will focus on developing methods for analysis and retrieval of human activities in video databases that also can facilitate efficient means for highly compressed storage. For this purpose, it is proposed to develop a novel representation method for human activities. Such a representation is termed as action script and it includes a detailed sequence of human actions that fully describe the 3D motions of all the major body parts. Action scripts can be extended to describe actions of multiple persons as well and could also become an innovative means for highly efficient summarization, retrieval and recognition of complex human activities in video databases.Another objective of this proposal is to develop innovative querying tools that facilitate efficient definition and retrieval of single/multi person activities in video databases. The approach proposed is founded on an extension of an innovative method, recently developed by the PI, forRecognition of human activity by Indexing and Sequencing (RISq). The RISq requires only few video samples and provides fast and robust recognition even in conditions of partial occlusion and varying speeds. It is proposed to further extend the RISq method for the proposed generation and recognition of action scripts of individuals and groups. This is an entirely unexplored domain that could lead to significant scientific contributions in analysis and management of video databases.

这个项目将侧重于发展分析和检索视像数据库中的人类活动的方法，这些方法也可以促进高度压缩存储的有效手段。为此，提出了一种新的人类活动表征方法。这种表现形式被称为动作脚本，它包括详细的人类动作序列，充分描述了所有主要身体部位的3D运动。动作脚本可以扩展到描述多人的动作，也可以成为视频数据库中对复杂的人类活动进行高效总结、检索和识别的创新手段。本提案的另一个目标是开发创新的查询工具，以促进视频数据库中单人/多人活动的有效定义和检索。提出的方法是基于PI最近开发的一种创新方法的扩展，用于通过索引和测序（RISq）识别人类活动。RISq只需要很少的视频样本，即使在部分遮挡和变化速度的条件下也能提供快速和强大的识别。建议进一步扩展RISq方法，以生成和识别个人和群体的动作脚本。这是一个完全未开发的领域，可能会在视频数据库的分析和管理方面产生重大的科学贡献。