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Journal of Electrical and Computer Engineering
Volume 2018, Article ID 3839104, 10 pages
https://doi.org/10.1155/2018/3839104
Research Article

A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

1School of Computer Science, Beijing Information Science and Technology University, Beijing, China
2Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, School of Computer Science, Beijing Information Science and Technology University, Beijing, China

Correspondence should be addressed to Xin Chen; nc.ude.utsib@nixnehc

Received 6 November 2017; Revised 30 January 2018; Accepted 19 February 2018; Published 8 April 2018

Academic Editor: Attila Kertesz

Copyright © 2018 Shengcheng Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper investigates and analyzes the characteristics of video data and puts forward a campus surveillance video storage system with the university campus as the specific application environment. Aiming at the challenge that the content-based video retrieval response time is too long, the key-frame index subsystem is designed. The key frame of the video can reflect the main content of the video. Extracted from the video, key frames are associated with the metadata information to establish the storage index. The key-frame index is used in lookup operations while querying. This method can greatly reduce the amount of video data reading and effectively improves the query’s efficiency. From the above, we model the storage system by a stochastic Petri net (SPN) and verify the promotion of query performance by quantitative analysis.