Space-time spectral model for object detection in dynamic textured background

被引：14

作者：

Ali, Imtiaz ^{[1
,2
,4
]}

Mille, Julien ^{[2
,3
]}

Tougne, Laure ^{[1
,2
]}

机构：

[1] Univ Lyon 2, LIRIS, UMR5205, F-69676 Lyon, France

[2] Univ Lyon, CNRS, Lyon, France

[3] Univ Lyon 1, LIRIS, UMR5205, F-69622 Villeurbanne, France

[4] Opt Labs, Islamabad, Pakistan

来源：

PATTERN RECOGNITION LETTERS | 2012年 / 33卷 / 13期

关键词：

Background model; Local Fourier transform; Dynamic texture; Object detection; SEGMENTATION; CLASSIFICATION; SCALE;

D O I：

10.1016/j.patrec.2012.06.011

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Background models are used for object detection in many computer vision algorithms. In this article, we propose a novel background modeling method based on frequency for spatially varying and time repetitive textured background. The local Fourier transform is applied to construct a pixel-wise representation of local frequency components. We apply our method for object detection in moving background conditions. Experimental results of our frequency-based background model are evaluated both qualitatively and quantitatively. (c) 2012 Elsevier B.V. All rights reserved.

引用

页码：1710 / 1716

页数：7

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