A Scalable and Robust Framework for Intelligent Real-time Video\n Surveillance

2016/10/29 by Shreenath Dutt, Dutt, Shreenath, Ankita Kalra +1
Computer Science · #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #Distributed #FOS: Computer and information sciences #Parallel #Video Analysis and Summarization #Video Surveillance and Tracking Methods #and Cluster Computing (cs.DC)

paper · pdf · doi:10.48550/arxiv.1610.09590

openalex publication_date 2016/10/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper, we present an intelligent, reliable and storage-efficient\nvideo surveillance system using Apache Storm and OpenCV. As a Storm topology,\nwe have added multiple information extraction modules that only write important\ncontent to the disk. Our topology is extensible, capable of adding novel\nalgorithms as per the use case without affecting the existing ones, since all\nthe processing is independent of each other. This framework is also highly\nscalable and fault tolerant, which makes it a best option for organisations\nthat need to monitor a large network of surveillance cameras.\n

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