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释视频并真实的检测意外活动。现有的监控摄像头无法解读视频。因为大多数都没有被真实的监控，所以它们在提高安全响应时间方面没有任何作用。该项目计划开发算法，从连续视频中的任何摄像头视角检测动作，这是智能监控所必需的功能，但在当前技术中却缺失。这将改善对需要立即关注的事件（如犯罪和医疗紧急情况）的安全响应时间，并为老年人护理，智能家居，儿童看护，患者监测和创伤后康复提供自主辅助。