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Optical Engineering

Kernel bandwidth estimation for moving object detection in non-stabilized cameras
Author(s): Carlos Cuevas; Raúl Mohedano; Narciso García
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Paper Abstract

Sophisticated strategies have been recently proposed for the detection of moving objects in non-stabilized camera setups. These strategies model both, background and foreground, using spatio-temporal non-parametric estimation. However, as no appropriate methods for dynamical kernel bandwidth are available, high-quality results cannot be obtained in all situations. Here, an automatic and efficient kernel bandwidth estimation strategy for spatio-temporal modeling is proposed. Background kernel bandwidth is estimated via a novel statistical analysis of spatially weighted data distributions, whereas foreground kernel bandwidth is estimated using a mean shift based analysis of previously detected foreground regions.

Paper Details

Date Published: 6 April 2012
PDF: 4 pages
Opt. Eng. 51(4) 040501 doi: 10.1117/1.OE.51.4.040501
Published in: Optical Engineering Volume 51, Issue 4
Show Author Affiliations
Carlos Cuevas, Univ. Politécnica de Madrid (Spain)
Raúl Mohedano, Univ. Politécnica de Madrid (Spain)
Narciso García, Univ. Politécnica de Madrid (Spain)


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