用视觉理解上下文，智能判断事件严重程度
Context-Aware Detection of Mixed Critical Events using Video Classification
- 通过上下文感知分析，动态判断事件严重性
- 在交通与火灾场景中验证了系统适应性
- 适合智能城市自动化监控系统部署
通过计算机视觉检测混合关键事件具有挑战性，因为需要理解上下文才能准确评估事件严重程度。混合关键事件（如不同程度的火灾或交通事故）要求系统具备上下文理解能力，以触发适当响应。本文提出一种适用于智慧城市应用的通用检测系统，在交通与火灾检测场景中进行了测试。主要贡献包括对检测需求的分析，以及开发出可适配多种应用场景的系统，推动了智能城市自动化监控的发展。
原文摘要 · Abstract (English)
Detecting mixed-critical events through computer vision is challenging due to the need for contextual understanding to assess event criticality accurately. Mixed critical events, such as fires of varying severity or traffic incidents, demand adaptable systems that can interpret context to trigger appropriate responses. This paper addresses these challenges by proposing a versatile detection system for smart city applications, offering a solution tested across traffic and fire detection scenarios. Our contributions include an analysis of detection requirements and the development of a system adaptable to diverse applications, advancing automated surveillance for smart cities.
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