[1]赵立双 冯莹 曹毓.单目视觉定位中SURF算法参数的优化[J].计算机技术与发展,2012,(06):6-9.
 ZHAO Li-shuang,FENG Ying,CAO Yu.Optimization of SURF Parameters in Monocular Visual Odometry[J].,2012,(06):6-9.
点击复制

单目视觉定位中SURF算法参数的优化()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年06期
页码:
6-9
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Optimization of SURF Parameters in Monocular Visual Odometry
文章编号:
1673-629X(2012)06-0006-04
作者:
赵立双 冯莹 曹毓
国防科学技术大学光电科学与工程学院
Author(s):
ZHAO Li-shuang FENG Ying CAO Yu
College of Optoelectronics Science and Eng. , National Univ. of Defense Techn
关键词:
机器视觉单目视觉定位SURF参数hessian矩阵行列式阈值
Keywords:
machine vision monocular visual odometry SURF parameters hessian threshold
分类号:
TP212.14
文献标志码:
A
摘要:
为了提升单目视觉定位方法的定位效率,在基于SURF算法的单目视觉定位系统上对SURF算法参数的选取进行了优化。首先分析了路面图像的特点及路面图像中SURF特征点的特性,据此选取了SURF算法中组数和层数这两个重要参数;其次分析了路面序列图像中特征点数目与hessian矩阵行列式阈值之间的关系,提出了hessian矩阵行列式阈值动态设定方法。通过对SURF算法参数的优化,有效降低了程序的运算量。实验结果表明,该方法能较好满足路面环境下定位的要求,在保证算法精度和稳定性的同时,大幅提高了程序的效率
Abstract:
In order to increase the localization frequency of monocular visual odometry, optimization of SURF parameters was done on monocular visual odometry system based on SURF. Firstly, features of pavement image and the SURF keypoint in it were analyzed, and octave number and octave layer number of SURF were properly chosen. Secondly, the relation between SURF keypoint number and hessian threshold in image sequence was analyzed,and a method of hessian threshold dynamic setting was put forward. By optimizing SURF "parameter,the amount of computation was reduced efficiently. The experimental results demonstrate that the method can fit the demand of localization on the pavement, meanwhile, the efficiency of monocular visual odometry is greatly improved as the accuracy and stability are well kept

相似文献/References:

[1]王明平 宋丽梅.基于计算机视觉的车架号采集系统[J].计算机技术与发展,2008,(04):239.
 WANG Ming-ping,SONG Li-mei.Vehicle Identify Number Acquisition System Based on Machine-Vision[J].,2008,(06):239.
[2]蒋恩松 肖辉军 孙刘杰 熊清廉.基于机器视觉的套印误差自动检测系统设计[J].计算机技术与发展,2008,(07):173.
 JIANG En-song,XIAO Hui-jun,SUN Liu-jie,et al.Design of Automatic Detecting Printing Registration Deviation System Based on Machine Vision[J].,2008,(06):173.
[3]张锦娟 师军 于佳丽 卢照.SpikeNet的研究及其在快速人脸识别中的应用[J].计算机技术与发展,2010,(07):235.
 ZHANG Jin-juan,SHI Jun,YU Jia-li,et al.Research on SpikeNet and Its Application in Quick Face Recognition[J].,2010,(06):235.
[4]方鹤鹤 冯宏伟 马煜.基于形态滤波和分水岭变换的边缘检测方法[J].计算机技术与发展,2006,(01):49.
 FANG He-he,FENG Hong-wei,MA Yu.Edge Detection Method Based on Morphology Filter and Watershed[J].,2006,(06):49.
[5]李雪晨 汪仁煌 艾星芳.改进的弯曲度算法在阶梯修剪检测中的应用[J].计算机技术与发展,2012,(03):166.
 LI Xue-chen,WANG Ren-huang,AI Xing-fang.Use of Improved Tortuosity Algorithm in Step Form Disfigurement Test[J].,2012,(06):166.
[6]徐自越 李战明 李二超.OpenCV在焊缝实时检测与处理系统中的应用[J].计算机技术与发展,2012,(08):170.
 XU Zi-yue,LI Zhan-ming,LI Er-chao.Application of OpenCV on Real-time Detection and Processing System of Seam[J].,2012,(06):170.
[7]杨杰,卢盛林,赵晓芳.机器视觉在钢化玻璃缺陷检测中的应用研究[J].计算机技术与发展,2013,(03):211.
 YANG Jie,LU Sheng-lin,ZHAO Xiao-fang.Application and Research of Machine Vision in Tempered Glass Defect Inspection[J].,2013,(06):211.
[8]陈鹏宇[],孙文奇[],赵忠龙[]. 基于机器视觉的印刷质量检测研究[J].计算机技术与发展,2014,24(07):103.
 CHEN Peng-yu[],SUN Wen-qi[],ZHAO Zhong-long[]. rinting Quality Detection Based on Machine Vision[J].,2014,24(06):103.
[9]洪磊[],嵇保健[],洪峰[]. 一种基于亚像素角点的 SIFT 立体匹配算法研究[J].计算机技术与发展,2016,26(01):48.
 HONG Lei[],JI Bao-jian[],HONG Feng[]. Research on a SIFT Stereo Matching Algorithm Based on Sub-pixel Corners[J].,2016,26(06):48.
[10]张哲,朱铮涛,李渊,等. 瓶盖缺陷在线自动检测技术研究[J].计算机技术与发展,2016,26(06):151.
 ZHANG Zhe,ZHU Zheng-tao,LI Yuan,et al. Research on Online Automatic Detecting Technology for Bottle Cap Defects[J].,2016,26(06):151.

备注/Memo

备注/Memo:
中国人民解放军总后勤部资助项目(BY2008J018)赵立双(1985-),男,硕士研究生,研究方向为光电测控技术;冯莹,教授,博士生导师,研究方向为宽带光纤光源技术、光纤激光器技术、光纤波导生物传感器技术以及光电测控技术
更新日期/Last Update: 1900-01-01