Vision and Crowdsensing Technology for an Optimal Response in Physical-Security
| Autor: | Fernando Sancho Caparrini, Juan Antonio Álvarez-García, Noelia Vallez, Oscar Deniz, Fernando Enríquez, Francisco Velasco, Luis Miguel Soria |
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| Přispěvatelé: | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos, Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | idUS: Depósito de Investigación de la Universidad de Sevilla Universidad de Sevilla (US) idUS. Depósito de Investigación de la Universidad de Sevilla instname Lecture Notes in Computer Science ISBN: 9783030227494 ICCS (5) |
| Popis: | Law enforcement agencies and private security companies work to prevent, detect and counteract any threat with the resources they have, including alarms and video surveillance. Even so, there are still terrorist attacks or shootings in schools in which armed people move around a venue exercising violence and generating victims, showing the limitations of current systems. For example, they force security agents to monitor continuously all the images coming from the installed cameras, and potential victims nearby are not aware of the danger until someone triggers a general alarm, which also does not give them information on what to do to protect themselves. In this article we present a project that is being developed to apply the latest technologies in early threat detection and optimal response. The system is based on the automatic processing of video surveillance images to detect weapons and a mobile app that serves both for detection through the analysis of mobile device sensors, and to send users personalised and dynamic indications. The objective is to react in the shortest possible time and minimise the damage suffered. |
| Databáze: | OpenAIRE |
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