Versatile Bayesian classifier for moving object detection by non-parametric background-foreground modeling

Cuevas Rodríguez, Carlos and Mohedano del Pozo, Raúl and García Santos, Narciso (2012). Versatile Bayesian classifier for moving object detection by non-parametric background-foreground modeling. In: "19th IEEE International Conference on Image Processing (ICIP)", 30/09/2012 - 03/10/2012, Orlando, Florida, USA. pp. 313-316. https://doi.org/10.1109/ICIP.2012.6466858.

Description

Title: Versatile Bayesian classifier for moving object detection by non-parametric background-foreground modeling
Author/s:
  • Cuevas Rodríguez, Carlos
  • Mohedano del Pozo, Raúl
  • García Santos, Narciso
Item Type: Presentation at Congress or Conference (Article)
Event Title: 19th IEEE International Conference on Image Processing (ICIP)
Event Dates: 30/09/2012 - 03/10/2012
Event Location: Orlando, Florida, USA
Title of Book: 19th IEEE International Conference on Image Processing (ICIP)
Date: 2012
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Along the recent years, several moving object detection strategies by non-parametric background-foreground modeling have been proposed. To combine both models and to obtain the probability of a pixel to belong to the foreground, these strategies make use of Bayesian classifiers. However, these classifiers do not allow to take advantage of additional prior information at different pixels. So, we propose a novel and efficient alternative Bayesian classifier that is suitable for this kind of strategies and that allows the use of whatever prior information. Additionally, we present an effective method to dynamically estimate prior probability from the result of a particle filter-based tracking strategy.

More information

Item ID: 23479
DC Identifier: http://oa.upm.es/23479/
OAI Identifier: oai:oa.upm.es:23479
DOI: 10.1109/ICIP.2012.6466858
Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6466858
Deposited by: Memoria Investigacion
Deposited on: 13 Apr 2014 07:46
Last Modified: 21 Apr 2016 23:17
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