Achieving $\epsilon$-Object Indistinguishability in Surveillance Videos Through Trajectory Randomization

IF 11.7 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Industrial Informatics Pub Date : 2024-11-26 DOI:10.1109/tii.2024.3495789

Medhavi Srivastava, Debanjan Sadhya

引用次数: 0

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通过轨迹随机化实现监控视频中的$\epsilon$-物体不可区分性

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Industrial Informatics 工程技术-工程：工业

CiteScore

24.10

自引率

8.90%

发文量

1202

审稿时长

5.1 months

期刊介绍： The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.