Next Generation Smart Camera Networks

下一代智能相机网络

• 批准号: RGPIN-2015-04533
• 负责人: Qureshi, Faisal
• 金额: $ 1.31万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=613017
• 关键词: Next; Generation; Smart; Camera; Networks

Camera networks have received much attention in recent years, in part due to their suitability in a wide range of applications. We also bear witness to a sudden increase in the availability of camera-equipped mobile devices. The immediate access to cameras creates new opportunities for designing the next generation of Smart Camera Networks (SCNs) capable of unattended operation and supporting new forms of collaborative sensing over expansive areas. We propose to develop scientific & theoretical foundations, investigate new methods, and research design principles needed to develop such camera networks. Control and coordination in SCNs: We will develop scientific theory and mathematical machinery to study and characterize distributed sensing and control in ad hoc networks of non-stationary smart cameras, focusing in particular upon new models for collaborative sensing in such networks. Networks of camera-equipped mobile devices: We will explore design principles and develop mathematical underpinnings for setting up short-duration, tasks-specific, ad hoc camera networks of transient and highly dynamic camera-equipped mobile devices in a manner that does not adversely affect the usability, battery-life, security, and privacy of these devices. Crowd tracking and scene understanding in SCNs: We will develop scientific and theoretical foundations for dense crowd tracking using ad hoc networks of non-stationary, smart cameras. In particular, we will explore “analysis via synthesis” approaches for dense crowd tracking in camera networks, where virtual crowd simulations exhibiting the statistical properties of the observed crowd will be used to refine crowd analysis and facilitate scene understanding. I envision significant benefits and numerous applications of this research program. The proposed research program provides many opportunities for unique and interdisciplinary HQP training. Furthermore, the outcomes of this program will directly benefit both local & international camera technology, video analytics, and digital entertainment industries. E.g., the theory and algorithms developed here will lead to more capable camera-equipped consumer devices that will support new forms of participatory sensing and collaborative scene analysis. Scientific, algorithmic, and technical contributions of this program will increase our understanding of distributed, collaborative scene analysis in large-scale ad hoc networks of non-stationary cameras, benefitting the wider camera networks and computer vision communities. This proposal aims to carryout highly original, fundamental scientific and technical research needed to realize the next generation of smart camera networks, and my existing work on camera networks and image analysis makes me an ideal candidate for pursuing the goals identified herein.

近年来，摄像机网络受到了广泛的关注，部分原因是它们适用于广泛的应用。我们还见证了配备摄像头的移动的设备的突然增加。对摄像机的即时访问为设计下一代智能摄像机网络（SCN）创造了新的机会，这些网络能够无人值守运行，并支持在广阔区域进行新形式的协作感知。我们建议发展科学和理论基础，研究新方法，并研究开发此类相机网络所需的设计原则。 SCN中的控制和协调：我们将开发科学理论和数学机器，以研究和表征非固定智能相机的ad hoc网络中的分布式传感和控制，特别关注这种网络中协作传感的新模型。 配备摄像头的移动的设备的网络：我们将探索设计原则，并开发数学基础，以建立短暂的，特定于任务的，临时的摄像头网络和高度动态的配备摄像头的移动的设备的方式，不会对这些设备的可用性，电池寿命，安全性和隐私产生不利影响。 SCN中的人群跟踪和场景理解：我们将使用非固定智能摄像机的ad hoc网络为密集人群跟踪开发科学和理论基础。特别是，我们将探索“通过合成分析”的方法，在摄像机网络中密集人群跟踪，其中虚拟人群模拟展示所观察到的人群的统计特性将被用来完善人群分析，促进场景理解。 我设想了这项研究计划的重大好处和众多应用。拟议的研究计划提供了许多独特的和跨学科的HQP培训的机会。此外，该计划的成果将直接惠及本地和国际相机技术，视频分析和数字娱乐行业。例如，在一个示例中，这里开发的理论和算法将导致更有能力的配备相机的消费者设备，其将支持新形式的参与式感测和协作场景分析。该计划的科学，算法和技术贡献将增加我们对大型非固定摄像机自组织网络中分布式协作场景分析的理解，从而使更广泛的摄像机网络和计算机视觉社区受益。 该提案旨在开展实现下一代智能相机网络所需的高度原创性的基础科学和技术研究，我在相机网络和图像分析方面的现有工作使我成为追求本文所确定目标的理想候选人。