Parallel Computational Intelligence-Based Multi-Camera Surveillance System

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Title: Parallel Computational Intelligence-Based Multi-Camera Surveillance System
Authors: Orts-Escolano, Sergio | Garcia-Rodriguez, Jose | Morell, Vicente | Cazorla, Miguel | Azorin-Lopez, Jorge | García-Chamizo, Juan Manuel
Research Group/s: Informática Industrial y Redes de Computadores | Robótica y Visión Tridimensional (RoViT)
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Growing neural gas | Camera networks | Visual surveillance | GPU | CUDA | Multi-core
Knowledge Area: Arquitectura y Tecnología de Computadores | Ciencia de la Computación e Inteligencia Artificial
Issue Date: 11-Apr-2014
Publisher: MDPI
Citation: Journal of Sensor and Actuator Networks. 2014, 3(2): 95-112. doi:10.3390/jsan3020095
Abstract: In this work, we present a multi-camera surveillance system based on the use of self-organizing neural networks to represent events on video. The system processes several tasks in parallel using GPUs (graphic processor units). It addresses multiple vision tasks at various levels, such as segmentation, representation or characterization, analysis and monitoring of the movement. These features allow the construction of a robust representation of the environment and interpret the behavior of mobile agents in the scene. It is also necessary to integrate the vision module into a global system that operates in a complex environment by receiving images from multiple acquisition devices at video frequency. Offering relevant information to higher level systems, monitoring and making decisions in real time, it must accomplish a set of requirements, such as: time constraints, high availability, robustness, high processing speed and re-configurability. We have built a system able to represent and analyze the motion in video acquired by a multi-camera network and to process multi-source data in parallel on a multi-GPU architecture.
Sponsor: This work was partially funded by the Spanish Government DPI2013-40534-R grant and Valencian Government GV/2013/005 and University of Alicante UA GRE11-01 grants.
ISSN: 2224-2708
DOI: 10.3390/jsan3020095
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (
Peer Review: si
Publisher version:
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INV - RoViT - Artículos de Revistas

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