CAREER: Smart Cameras Getting Smarter: Detecting High-level Events Across Battery-powered Wireless Embedded Smart Cameras

职业：智能相机变得更加智能：通过电池供电的无线嵌入式智能相机检测高级事件

• 批准号: 1206291
• 负责人: Senem Velipasalar
• 金额: $ 40万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-06 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1206291&HistoricalAwards=false
• 关键词: CAREER; Smart; Cameras; Getting; Smarter

Visual surveillance is widely used in military and commercial applications, and public transportation scenarios. There are an estimated 30 million surveillance cameras in the U.S. capturing 4 billion hours of footage a week. The large amounts of video data generated by these cameras necessitate automatic detection of semantically high-level events, since the attention of a human operator watching multiple video feeds decreases over time. In addition, requiring cameras to have access to electrical outlets and to have wired links hinders system flexibility in terms of the number and placement of cameras, incurs significant costs, and limits possible applications and mobility. Embedded smart cameras allow us to deploy many spatially-distributed cameras interconnected by wireless links. A smart camera combines sensing, processing, and communication on a single embedded platform. Yet, it has very limited energy and processing power. The objective in this project is to build a battery-powered, self-adapting, wireless embedded smart camera system for the detection of semantically high-level events, which can span multiple overlapping or non-overlapping camera views, in a scalable and energy-efficient manner, and remove the dependence on wired links. Resource-aware and distributed object tracking and event detection algorithms, and self-adapting decision methodologies will be developed to decrease the energy consumption, and increase the battery-life of cameras. The outcomes are expected to have important positive impact, because they will fundamentally transform video surveillance and event detection solutions by addressing the privacy issues simultaneously. This technology can be used across disciplines and in wide-ranging areas, including next-generation cyber-physical systems, military and commercial applications, traffic analysis, health care and wildlife monitoring. Outreach to younger children is planned through the deployment of this project at the local Children?s Zoo and Museum.

视觉监控广泛应用于军事和商业应用以及公共交通场景。据估计，美国有3000万个监控摄像头，每周拍摄40亿小时的镜头。这些摄像机生成的大量视频数据需要自动检测语义上的高级事件，因为观看多个视频源的操作员的注意力会随着时间的推移而下降。此外，要求摄像机能够接入电源插座并且具有有线链路阻碍了系统在摄像机的数量和放置方面的灵活性，导致了显著的成本，并且限制了可能的应用和移动性。嵌入式智能摄像机使我们能够部署许多通过无线链路互连的空间分布式摄像机。智能相机在单个嵌入式平台上集成了传感、处理和通信功能。然而，它的能量和处理能力非常有限。该项目的目标是构建一个电池供电的、自适应的、无线嵌入式智能摄像机系统，用于检测语义上高级别的事件，该系统可以以可扩展和节能的方式跨越多个重叠或不重叠的摄像机视图，并消除对有线链路的依赖。将开发资源感知和分布式对象跟踪和事件检测算法以及自适应决策方法，以降低能耗，并增加相机的电池寿命。预计这些成果将产生重要的积极影响，因为它们将通过同时解决隐私问题从根本上改变视频监控和事件检测解决方案。该技术可用于跨学科和广泛的领域，包括下一代网络物理系统，军事和商业应用，交通分析，医疗保健和野生动物监测。计划通过在当地儿童？动物园和博物馆。

项目成果

Heat Mapping Drones: An Autonomous Computer-Vision-Based Procedure for Building Envelope Inspection Using Unmanned Aerial Systems (UAS)

热图无人机：一种基于计算机视觉的自主程序，用于使用无人机系统 (UAS) 进行建筑围护结构检查

• DOI: 10.1080/24751448.2018.1420963
• 发表时间: 2018
• 期刊: Technology|Architecture + Design
• 作者: Rakha, Tarek;Liberty, Amanda;Gorodetsky, Alice;Kakillioglu, Burak;Velipasalar, Senem
• 通讯作者: Velipasalar, Senem