Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios

用于高密度和遮挡场景中人群建模的自适应学习视觉传感器网络设计

• 批准号: LP100200430
• 负责人: Prof Marimuthu Palaniswami
• 金额: $ 18.04万
• 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: 2011
• 资助国家: 澳大利亚
• 起止时间: 2011-04-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP100200430
• 关键词: Design; adaptive; learning; visual; sensor

Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.

该项目与墨尔本大学的研究人员、视频监控专家SenSen、工程咨询公司ARUP和墨尔本板球俱乐部合作，致力于研究一个系统集成的现有监控基础设施，以模拟人群行为和退出策略，为场馆管理人员和应急服务提供实时分析、预测和响应能力。这种新的能力提高了安全资源的利用率，以防止在疏散情况下发生伤亡事故，适用于现有场馆，并影响全国各地新设施的发展。该项目提供研究人员培训，为当地技术提供全球客户，并为当地产业增长提供平台。