Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Adaptable Bayesian classifier for spatiotemporal nonparametric moving object detection strategies
Year:2012
Research Areas
  • Engineering,
  • Processing and signal analysis
Information
Abstract
Electronic devices endowed with camera platforms require new and powerful machine vision applications, which commonly include moving object detection strategies. To obtain high-quality results, the most recent strategies estimate nonparametrically background and foreground models and combine them by means of a Bayesian classifier. However, typical classifiers are limited by the use of constant prior values and they do not allow the inclusion of additional spatiodependent prior information. In this Letter, we propose an alternative Bayesian classifier that, unlike those reported before, allows the use of additional prior information obtained from any source and depending on the spatial position of each pixel.
International
Si
JCR
Si
Title
Optics Letters
ISBN
0146-9592
Impact factor JCR
3,385
Impact info
Volume
37
10.1364/OL.37.003159
Journal number
15
From page
3159
To page
3161
Month
AGOSTO
Ranking
49/77 OPTICS (SCI)
Participants
  • Autor: Carlos Cuevas Rodriguez (UPM)
  • Autor: Raúl Mohedano Del Pozo (UPM)
  • Autor: Narciso Garcia Santos (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
S2i 2019 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)