Kernel bandwidth estimation for moving object detection in non-stabilized cameras

Carlos Cuevas; Raúl Mohedano; Narciso García

doi:10.1117/1.OE.51.4.040501

6 April 2012 Kernel bandwidth estimation for moving object detection in non-stabilized cameras

Carlos Cuevas, Raúl Mohedano, Narciso García

Author Affiliations +

Optical Engineering, Vol. 51, Issue 4, 040501 (April 2012). https://doi.org/10.1117/1.OE.51.4.040501

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.

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Carlos Cuevas, Raúl Mohedano, and Narciso García "Kernel bandwidth estimation for moving object detection in non-stabilized cameras," Optical Engineering 51(4), 040501 (6 April 2012). https://doi.org/10.1117/1.OE.51.4.040501

Published: 6 April 2012

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