View and shape invariant modeling of human actions for smart surveillance

查看和塑造用于智能监控的人类行为的不变模型

• 批准号: DP160101458
• 负责人: Prof Ajmal Mian
• 金额: $ 20.52万
• 依托单位: The University of Western Australia
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-01-01 至 2019-10-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP160101458
• 关键词: View; shape; invariant; modeling; human

This project aims to enable surveillance cameras to interpret videos and detect unexpected activity in real time. Existing surveillance cameras are unable to interpret videos. Because most are not monitored in real time, they play no role in improving security response time. The project plans to develop algorithms to detect actions from any camera viewpoint in continuous videos, a capability that is imperative for smart surveillance yet missing in current techniques. This would improve security and safety response time to events that need immediate attention, such as crimes and medical emergencies, and offer autonomous aids to elderly care, smart homes, child minding, patient monitoring and post-trauma rehabilitation.

该项目旨在使监控摄像头能够解读视频并实时检测意外活动。现有的监控摄像头无法解读视频。由于大多数都不是实时监控的，因此它们对于提高安全响应时间没有起到任何作用。该项目计划开发算法来检测连续视频中任何摄像机视角的动作，这是智能监控所必需的功能，但在当前技术中却缺失。这将提高对犯罪和医疗紧急情况等需要立即关注的事件的安全响应时间，并为老年人护理、智能家居、儿童看护、患者监护和创伤后康复提供自主援助。