Real-time incidents detection in the highways of the future

Pecharromán Galindo, Antonio; Sánchez Almodóvar, Nuria; Torres Arjona, Juan y Menendez Garcia, Jose Manuel (2011). Real-time incidents detection in the highways of the future. En: "15th Portuguese Conference on Artificial Intelligence (EPIA 2011)", 10/10/2011 - 13/10/2011, Lisbon, Portugal. pp. 108-121.

Descripción

Título: Real-time incidents detection in the highways of the future
Autor/es:
  • Pecharromán Galindo, Antonio
  • Sánchez Almodóvar, Nuria
  • Torres Arjona, Juan
  • Menendez Garcia, Jose Manuel
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 15th Portuguese Conference on Artificial Intelligence (EPIA 2011)
Fechas del Evento: 10/10/2011 - 13/10/2011
Lugar del Evento: Lisbon, Portugal
Título del Libro: 15th Portuguese Conference on Artificial Intelligence (EPIA 2011)
Fecha: 2011
Materias:
Palabras Clave Informales: Stopped Vehicle Detection, Passenger and Driver Detection, Pedestrian Detection, Computer Vision, Highway traffic, Adaptive Background Subtraction. Deterministic Rules. Intelligent Transportation Systems
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Due to ever increasing transportation of people and goods, automatic traffic surveillance is becoming a key issue for both providing safety to road users and improving traffic control in an efficient way. In this paper, we propose a new system that, exploiting the capabilities that both computer vision and machine learning offer, is able to detect and track different types of real incidents on a highway. Specifically, it is able to accurately detect not only stopped vehicles, but also drivers and passengers leaving the stopped vehicle, and other pedestrians present in the roadway. Additionally, a theoretical approach for detecting vehicles which may leave the road in an unexpected way is also presented. The system works in real-time and it has been optimized for working outdoor, being thus appropriate for its deployment in a real-world environment like a highway. First experimental results on a dataset created with videos provided by two Spanish highway operators demonstrate the effectiveness of the proposed system and its robustness against noise and low-quality videos.

Más información

ID de Registro: 36941
Identificador DC: http://oa.upm.es/36941/
Identificador OAI: oai:oa.upm.es:36941
Depositado por: Memoria Investigacion
Depositado el: 01 Ago 2015 12:12
Ultima Modificación: 06 Jun 2016 12:12
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