@InProceedings{ChoqueluqueRomanCáma:2020:ViDeLo,
author = "Choqueluque Roman, David Gabriel and C{\'a}mara Ch{\'a}vez,
Guillermo",
affiliation = "Department of Computer Science, Universidad Cat{\'o}lica San
Pablo, Arequipa, Per{\'u} and Department of Computer Science,
Federal University of Ouro Preto, Ouro Preto, Brazil",
title = "Violence Detection and Localization in Surveillance Video",
booktitle = "Proceedings...",
year = "2020",
editor = "Musse, Soraia Raupp and Cesar Junior, Roberto Marcondes and
Pelechano, Nuria and Wang, Zhangyang (Atlas)",
organization = "Conference on Graphics, Patterns and Images, 33. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "Violence detection, violence localization, video surveillance,
dynamic images, video summarization, saliency detection.",
abstract = "Automatic violence detection in video surveillance is crucial for
social and personal security. Due to the massive video data
produced by surveillance cameras installed in different
environments like airports, trains, stadiums, schools, etc.,
traditional video monitoring by humans operators becomes
inefficient. In this context, develop systems capable of detect
automatically violent actions is a challenging task. This study
describes a method to detect and localize violent acts in video
surveillance using dynamic images, CNN's, and weakly supervised
localization methods. Experimental results demonstrate the
effectiveness of our approach when applied to three public
benchmark datasets: Hockey Fight, Violent Flows, and
UCFCrime2Local.",
conference-location = "Porto de Galinhas (virtual)",
conference-year = "7-10 Nov. 2020",
doi = "10.1109/SIBGRAPI51738.2020.00041",
url = "http://dx.doi.org/10.1109/SIBGRAPI51738.2020.00041",
language = "en",
ibi = "8JMKD3MGPEW34M/43BDNEB",
url = "http://urlib.net/ibi/8JMKD3MGPEW34M/43BDNEB",
targetfile = "107.pdf",
urlaccessdate = "2025, Feb. 16"
}