Monitoring a large surveillance space through distributed face matching

Richa Mishra, Prasanna Kumar, S. Chaudhury, I. Sreedevi
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引用次数: 14

Abstract

Large space with many cameras require huge storage and computational power to process these data for surveillance applications. In this paper we propose a distributed camera and processing based face detection and recognition system which can generate information for finding spatiotemporal movement pattern of individuals over a large monitored space. The system is built upon Hadoop Distributed File System using map reduce programming model. A novel key generation scheme using distance based hashing technique has been used for distribution of the face matching task. Experimental results have established effectiveness of the technique.
通过分布式人脸匹配实现对大监控空间的监控
有许多摄像机的大空间需要巨大的存储和计算能力来处理这些监控应用程序的数据。本文提出了一种基于分布式摄像头和处理的人脸检测与识别系统,该系统可以生成信息,用于在监测的大空间中寻找个体的时空运动模式。该系统基于Hadoop分布式文件系统,采用reduce编程模型。提出了一种基于距离哈希的密钥生成方案,用于人脸匹配任务的分配。实验结果证明了该技术的有效性。
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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