复杂环境中车辆检测与跟踪方法的研究

王齐; 金小峰

doi:10.3788/YJYXS20163105.0511

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复杂环境中车辆检测与跟踪方法的研究

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- 复杂环境中车辆检测与跟踪方法的研究
- Vehicle detecting and tracking method in complex environments
- 液晶与显示 2016年31卷第5期页码：511-517
- 作者机构：
  
  延边大学工学院计算机科学与技术系智能信息处理研究室, 吉林延吉,133002
- 作者简介：
  
  [ "王齐(1975-),男,吉林梨树人,硕士研究生,主要研究领域为智能信息处理。E-mail:wangqi@ybu.edu.cn" ]
  [ "金小峰(1970-),男,黑龙江东宁人,副教授,硕士研究生导师,主要研究领域为智能信息处理。E-mail:xfjin@ybu.edu.cn" ]
- 基金信息：
  
  吉林省科技厅自然科学基金(No.20140101225JC)()
- DOI：10.3788/YJYXS20163105.0511
  中图分类号： TP391.41
- 收稿日期：2015-05-19，
  
  修回日期：2015-08-17，
  
  纸质出版日期：2016-05-05
- 稿件说明：
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王齐, 金小峰,. 复杂环境中车辆检测与跟踪方法的研究[J]. 液晶与显示, 2016,31(5): 511-517

WANG Qi, JIN Xiao-feng,. Vehicle detecting and tracking method in complex environments[J]. , 2016,31(5): 511-517
王齐, 金小峰,. 复杂环境中车辆检测与跟踪方法的研究[J]. 液晶与显示, 2016,31(5): 511-517 DOI： 10.3788/YJYXS20163105.0511.

WANG Qi, JIN Xiao-feng,. Vehicle detecting and tracking method in complex environments[J]. , 2016,31(5): 511-517 DOI： 10.3788/YJYXS20163105.0511.

摘要

提出了一种在复杂环境中车辆检测与跟踪方法。该方法首先分析车辆的外形特点

确定采用从Blob块提取的几何形状参数作为车辆的特征并用于运动车辆的检测;然后结合Blob分析和CamShift算法提出了车辆跟踪方法。实验结果表明

本文采用的车辆特征参数能够准确地检测车辆

并能准确地区分车辆和行人群体

车辆检测与跟踪准确率分别达到了96.7%和86.7%

证明该方法适用于复杂环境下车辆的检测与跟踪应用要求。

Abstract

The paper proposes a method of vehicle detecting and tracking in complex environments. Firstly

by analyzing the vehicle external feature

the geometrical shape parameters extracted from its Blob blocks are employed to detect the moving vehicles. Then

vehicle tracking method is presented based on Blob analysis and CamShift algorithm. Experimental results show that the proposed method can detect the target vehicle and distinguish the vehicle and pedestrian accurately. The precision rate of vehicle detecting and tracking achieve 96.7% and 86.7% respectively

which prove that the method is appropriate for the demand of vehicle detecting and tracking in complex environments.

关键词

Keywords

references

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