Detecting Violent Robberies in CCTV Videos Using Deep Learning

Giorgio Morales, Itamar Salazar-Reque, Joel Telles, Daniel Díaz

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

14 Citas (Scopus)

Resumen

Video surveillance through security cameras has become difficult due to the fact that many systems require manual human inspection for identifying violent or suspicious scenarios, which is practically inefficient. Therefore, the contribution of this paper is twofold: the presentation of a video dataset called UNI-Crime, and the proposal of a violent robbery detection method in CCTV videos using a deep-learning sequence model. Each of the 30 frames of our videos passes through a pre-trained VGG-16 feature extractor; then, all the sequence of features is processed by two convolutional long-short term memory (convLSTM) layers; finally, the last hidden state passes through a series of fully-connected layers in order to obtain a single classification result. The method is able to detect a variety of violent robberies (i.e., armed robberies involving firearms or knives, or robberies showing different level of aggressiveness) with an accuracy of 96.69%.

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence Applications and Innovations - 15th IFIP WG 12.5 International Conference, AIAI 2019, Proceedings
EditoresElias Pimenidis, Ilias Maglogiannis, Lazaros Iliadis, John MacIntyre
EditorialSpringer New York LLC
Páginas282-291
Número de páginas10
ISBN (versión impresa)9783030198220
DOI
EstadoPublicada - 2019
Publicado de forma externa
Evento15th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2019 - Hersonissos, Grecia
Duración: 24 may. 201926 may. 2019

Serie de la publicación

NombreIFIP Advances in Information and Communication Technology
Volumen559
ISSN (versión impresa)1868-4238

Conferencia

Conferencia15th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2019
País/TerritorioGrecia
CiudadHersonissos
Período24/05/1926/05/19

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