DMSS: Towards Resource-Efficient Automated Video Surveillance Systems

CSR # 0834537, ？DMSS：迈向资源高效的自动化视频监控系统？[摘要]安全问题已成为地区、国家乃至全球关注的焦点。因此，人们对视频监控的兴趣急剧增长。自动视频监控是实时检测威胁并监控其进展的一种优雅而有效的方法。不幸的是，自动化、可扩展和大规模分布式监控系统的设计一直是一个重要的研究问题。功耗也是一个主要问题，特别是在电池供电的视频源中。本项目通过开发最优带宽分配方案来解决大规模监控系统的可扩展性成本和功耗问题，该方案考虑到潜在的威胁级别、视频源的放置、位置重要性、站点地图和视觉算法的率-精度曲线，控制各种视频源的传输速率。它还开发了一个模型，用于根据在一定时期内检测到的潜在威胁的统计汇总、它们的敏感性水平、检测到它们的位置的重要性以及它们与其他重要位置的接近程度来确定当前的总体警告级别。此外，该项目还研究了其他重要方面，包括分布式处理体系结构的容错、自适应流、特征提取和连续查询。通过解决可扩展性成本和功耗问题，并以内聚和集成的方式处理几个设计方面的问题，本研究为可扩展性和成本效益的自动化视频监控系统的设计提供了重要的贡献。此外，它还对国土安全、教育和代表性不足群体的参与产生了重大而广泛的影响。

CSR # 0834537, ?DMSS: Towards Resource-Efficient Automated Video Surveillance Systems?, PI: Nabil J. Sarhan AbstractThe security problem has emerged as a major concern regionally, nationally, and globally. Therefore, the interest in video surveillance has grown dramatically. Automated video surveillance serves as an elegant and efficient approach for realtime detection of threats and monitoring their progress. Unfortunately, the design of an automated, scalable, and massively distributed surveillance system has been a significant research problem. Power consumption has also been a primary concern, especially in battery-powered video sources. This project addresses the scalability-cost and power consumption problems of large-scale surveillance systems by developing optimal bandwidth allocation schemes, which control the transfer rates of various video sources, considering the potential threat level, placement of video sources, location importance, site map, and rate-accuracy curves of vision algorithms. It also develops a model for determining the current overall warning level based on statistical aggregation of the potential threats detected over a certain period, their levels of sensitivity, the importance of the locations where they are detected, and their closeness to other important locations. Additionally, this project investigates other important aspects, including fault tolerance of the distributed processing architecture, adaptive streaming, feature extraction, and continuous querying. By addressing the scalability-cost and power consumption problems and dealing with several design aspects in a cohesive and integrated manner, this research provides significant contributions in the design of scalable and cost-effective automated video surveillance systems. Furthermore, it has significant broader impacts on homeland security, education, and participation of underrepresented groups.