Road tracking using particle filters with partition sampling and auxiliary variables

被引：12

作者：

Bai, Li ^{[1
]}

Wang, Yan ^{[2
]}

机构：

[1] Univ Nottingham, Sch Comp Sci, Nottingham NG8 1BB, England

[2] Univ Bradford, Sch Comp Informat & Media, Bradford BD7 1DP, W Yorkshire, England

来源：

COMPUTER VISION AND IMAGE UNDERSTANDING | 2011年 / 115卷 / 10期

关键词：

Road tracking; Particle filter; Partition sampling; LANE DETECTION; VISION; CONDENSATION; ASSISTANCE;

D O I：

10.1016/j.cviu.2011.06.005

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we present a novel algorithm for road tracking using computer vision techniques. We have extended the sampling algorithm used in the standard particle filter and integrated our new algorithm into a multiple tracker framework for road tracking. The standard particle filters use Sampling Importance Resampling (SIR) to draw particles from an importance proposal density function. Experimental results show that our method. is accurate and is suitable for real road applications. (C) 2011 Elsevier Inc. All rights reserved.

引用

页码：1463 / 1471

页数：9

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