A LOW RESOLUTION MULTI-CAMERA SYSTEM FOR PERSON TRACKING

被引：0

作者：

Eldih, Mohamed ^{[1
,2
]}

Bo, Nyan Bo ^{[1
,2
]}

Dehoeverie, Francis ^{[1
,2
]}

Nino, Jorge ^{[1
,2
]}

Guan, Junzhi ^{[1
,2
]}

Van de Velde, Samuel ^{[1
]}

Steendam, Heidi ^{[1
]}

Aghajan, Hamid ^{[1
,3
]}

Philips, Wilfried ^{[1
,2
]}

机构：

[1] Ghent Univ iMinds, Dept Telecommun & Informat Proc, Ghent, Belgium

[2] Stanford Univ, Image Proc & Interpretat Vis Syst, Stanford, CA 94305 USA

[3] Stanford Univ, Ambient Intelligence Res Lab, Stanford, CA 94305 USA

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2014年

关键词：

Low resolution multi-camera systems; behavior analysis; tracking; foreground detection;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The current multi-camera systems have not studied the problem of person tracking under low resolution constraints. In this paper, we propose a low resolution sensor network for person tracking. The network is composed of cameras with a resolution of 30x30 pixels. The multi-camera system is used to evaluate probability occupancy mapping and maximum likelihood trackers against ground truth collected by ultra-wideband (UWB) testbed. Performance evaluation is performed on two video sequences of 30 minutes. The experimental results show that maximum likelihood estimation based tracker outperforms the state-of-the-art on low resolution cameras.

引用

页码：378 / 382

页数：5

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