Scalable Robust Video Surveillance over Constrained Networks

在受限网络上进行可扩展的鲁棒视频监控

• 批准号: LP0883417
• 负责人: Prof William Moran
• 金额: $ 27.21万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2008
• 资助国家: 澳大利亚
• 起止时间: 2008-11-11 至 2013-01-07
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0883417
• 关键词: Scalable; Robust; Video; Surveillance; over

Real-time monitoring of large numbers of people is becoming increasingly important for applications such as efficient service delivery and security against both common crime and terrorism. The use of human operators for such tasks is infeasible due to the large amount of data collected. Existing autonomous video surveillance systems are prone to high numbers of false alarms and often require expensive hardware. This proposal seeks to address both difficulties by using rigorous statistical signal processing methods to optimally fuse information from a network of low-cost cameras.

对大量人员的实时监控对于诸如有效的服务提供和针对常见犯罪和恐怖主义的安全性等应用变得越来越重要。 由于收集的数据量大，使用人类操作员进行此类任务是不可行的。 现有的自主视频监控系统容易出现大量的错误警报，并且通常需要昂贵的硬件。 该提案试图通过使用严格的统计信号处理方法来解决这两个困难，以最佳方式融合来自低成本摄像机网络的信息。