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Reference TypeConference Paper (Conference Proceedings)
Last Update2015: (UTC) administrator
Metadata Last Update2016: (UTC) administrator
Citation KeyAlmeidaVida:2015:ClNãEv
TitleClassificação não-supervisionada de eventos em imagens de videomonitoramento baseada em altas frequências do fluxo ótico diferencial
Access Date2022, Jan. 28
Number of Files1
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Context area
Author1 Almeida, Ana Paula Gonçalves S. de
2 Vidal, Flavio de Barros
Affiliation1 Programa de Pós-Graduação em Sistemas Mecatrônicos - Universidade de Brasília
2 Departamento de Ciência da Computação - Universidade de Brasilia
EditorRios, Ricardo Araujo
Paiva, Afonso
Conference NameConference on Graphics, Patterns and Images, 28 (SIBGRAPI)
Conference LocationSalvador
DateAug. 26-29, 2015
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeWork in Progress
History (UTC)2015-07-13 13:26:54 :: -> administrator ::
2016-06-03 21:18:36 :: administrator -> :: 2015
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Keywordsevent classification
motion analysis
optical flow
AbstractEvents related to vandalism and violence often occur in crowded environments and mostly in unstructured environments (dynamic). The use of security cameras in crowd monitoring analysis for anomaly detection and alarms could be an efficient and inexpensive method. The goal of this paper is to build an unsupervised classification method to abnormal events that is robust and stable. The main idea is based on analysis of Fourier Transform's high-frequency spatial components features of optical flow, allowing the detection of abnormal acts in surveillance videos. Preliminary results show that the proposed methodology is capable of successfully execute the process of detection, permitting the development of an efficient recognition stage for future works. > SDLA > SIBGRAPI 2015 > Classificação não-supervisionada de...
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Next Higher Units8JMKD3MGPBW34M/3K24PF8
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