Application of portrait recognition system for emergency evacuation in mass emergencies

A portrait recognition system can play an important role in emergency evacuation in mass emergencies. This paper designed a portrait recognition system, analyzed the overall structure of the system and the method of image preprocessing, and used the Single Shot MultiBox Detector (SSD) algorithm for...

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Autor principal:	Xu Ke
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	portrait recognition system unexpected incidents emergency evacuation ssd algorithm pca Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/7ae82095c5d9417a9b403a691141a99b
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spelling	oai:doaj.org-article:7ae82095c5d9417a9b403a691141a99b2021-12-05T14:10:51ZApplication of portrait recognition system for emergency evacuation in mass emergencies2191-026X10.1515/jisys-2021-0052https://doaj.org/article/7ae82095c5d9417a9b403a691141a99b2021-07-01T00:00:00Zhttps://doi.org/10.1515/jisys-2021-0052https://doaj.org/toc/2191-026XA portrait recognition system can play an important role in emergency evacuation in mass emergencies. This paper designed a portrait recognition system, analyzed the overall structure of the system and the method of image preprocessing, and used the Single Shot MultiBox Detector (SSD) algorithm for portrait detection. It also designed an improved algorithm combining principal component analysis (PCA) with linear discriminant analysis (LDA) for portrait recognition and tested the system by applying it in a shopping mall to collect and monitor the portrait and establish a data set. The results showed that the missing detection rate and false detection rate of the SSD algorithm were 0.78 and 2.89%, respectively, which were lower than those of the AdaBoost algorithm. Comparisons with PCA, LDA, and PCA + LDA algorithms demonstrated that the recognition rate of the improved PCA + LDA algorithm was the highest, which was 95.8%, the area under the receiver operating characteristic curve was the largest, and the recognition time was the shortest, which was 465 ms. The experimental results show that the improved PCA + LDA algorithm is reliable in portrait recognition and can be used for emergency evacuation in mass emergencies.Xu KeDe Gruyterarticleportrait recognition systemunexpected incidentsemergency evacuationssd algorithmpcaScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 893-902 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	portrait recognition system unexpected incidents emergency evacuation ssd algorithm pca Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	portrait recognition system unexpected incidents emergency evacuation ssd algorithm pca Science Q Electronic computers. Computer science QA75.5-76.95 Xu Ke Application of portrait recognition system for emergency evacuation in mass emergencies
description	A portrait recognition system can play an important role in emergency evacuation in mass emergencies. This paper designed a portrait recognition system, analyzed the overall structure of the system and the method of image preprocessing, and used the Single Shot MultiBox Detector (SSD) algorithm for portrait detection. It also designed an improved algorithm combining principal component analysis (PCA) with linear discriminant analysis (LDA) for portrait recognition and tested the system by applying it in a shopping mall to collect and monitor the portrait and establish a data set. The results showed that the missing detection rate and false detection rate of the SSD algorithm were 0.78 and 2.89%, respectively, which were lower than those of the AdaBoost algorithm. Comparisons with PCA, LDA, and PCA + LDA algorithms demonstrated that the recognition rate of the improved PCA + LDA algorithm was the highest, which was 95.8%, the area under the receiver operating characteristic curve was the largest, and the recognition time was the shortest, which was 465 ms. The experimental results show that the improved PCA + LDA algorithm is reliable in portrait recognition and can be used for emergency evacuation in mass emergencies.
format	article
author	Xu Ke
author_facet	Xu Ke
author_sort	Xu Ke
title	Application of portrait recognition system for emergency evacuation in mass emergencies
title_short	Application of portrait recognition system for emergency evacuation in mass emergencies
title_full	Application of portrait recognition system for emergency evacuation in mass emergencies
title_fullStr	Application of portrait recognition system for emergency evacuation in mass emergencies
title_full_unstemmed	Application of portrait recognition system for emergency evacuation in mass emergencies
title_sort	application of portrait recognition system for emergency evacuation in mass emergencies
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/7ae82095c5d9417a9b403a691141a99b
work_keys_str_mv	AT xuke applicationofportraitrecognitionsystemforemergencyevacuationinmassemergencies
_version_	1718371674204667904

Application of portrait recognition system for emergency evacuation in mass emergencies

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