A flood detection and warning system based on video content analysis

Martin Joshua P. San Miguel, Conrado R. Ruiz*

*Autor correspondiente de este trabajo

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

Floods are becoming more frequent and extreme due to climate change. Early detection is critical in providing a timely response to prevent damage to property and life. Previous methods for flood detection make use of specialized sensors or satellite imagery. In this paper, we propose a method for event detection based on video content analysis of feeds from surveillance cameras, which have become more common and readily available. Since these cameras are static, we can use image masks to identify regions of interest in the video where the flood would likely occur. We then perform background subtraction and then use image segmentation on the foreground region. The main features of the segment that we use to identify if it is a flooded region are: color, size and edge density. We use a probabilistic model of the color of the flood based on our set of collected flood images. We determine the size of the segment relative to the frame size as another indicator that it is flood since flooded regions tend to occupy a huge region of the frame. Finally, we perform a form of ripple detection by performing edge detection and using the edge density as a possible indicator for ripples and consequently flood. We then broadcast an SMS message after detecting a flood event consistently across multiple frames for a specified time period. Our results show that this simple technique can adequately detect floods in real-time.

Idioma originalInglés
Título de la publicación alojadaAdvances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings
EditoresGeorge Bebis, Darko Koracin, Tobias Isenberg, Sandra Skaff, Amela Sadagic, Richard Boyle, Fatih Porikli, Jianyuan Min, Carlos Scheidegger, Alireza Entezari, Bahram Parvin, Daisuke Iwai
EditorialSpringer Verlag
Páginas65-74
Número de páginas10
ISBN (versión impresa)9783319508313
DOI
EstadoPublicada - 2016
Publicado de forma externa
Evento12th International Symposium on Visual Computing, ISVC 2016 - Las Vegas, Estados Unidos
Duración: 12 dic 201614 dic 2016

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen10073 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia12th International Symposium on Visual Computing, ISVC 2016
País/TerritorioEstados Unidos
CiudadLas Vegas
Período12/12/1614/12/16

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