[1]毛雁明 杨慧玲.一种新的立体匹配算法[J].计算机技术与发展,2011,(03):105-108.
　MAO Yan-ming,YANG Hui-ling.A New Stereo Matching Algorithm[J].,2011,(03):105-108.
点击复制

一种新的立体匹配算法()
分享到：

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

卷:
期数:
2011年03期
页码:
105-108
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
A New Stereo Matching Algorithm
文章编号:
1673-629X（2011）03-0105-04
作者:
毛雁明 杨慧玲
宁德师范学院计算机与信息工程系
Author(s):
MAO Yan-ming;  YANG Hui-ling
Computer and Information Engineering Department of Ningde Normal University
关键词:
计算机视觉; Harris; LMedS; 立体匹配; 匹配点距离相关性
Keywords:
computer vision;  Harris ;  LMedS ;  stereo matching ;  distance correlation of matching points
分类号:
TP301.6
文献标志码:
A
摘要:
立体匹配是目前计算机视觉领域中最活跃的研究主题之一，在三维重构、对象识别与分类、图像对齐等应用中，立体匹配都是一个关键步骤。为了能够更精确地对特征点进行匹配，给出了一个新的匹配约束条件：匹配点距离相关性约束，据此提出了一种新的立体匹配算法。该算法独立于特征点的检测算法，首先使用灰度相关法进行初始匹配，然后利用最小中值平方法获得部分正确匹配点集，在此基础上加入匹配点距离相关性约束进行引导匹配，得到最后的匹配点集。实验表明，该算法能够很好地实现特征点的正确匹配，具有很高的使用价值
Abstract:
Stereo matching is still the most active research theme in the field of computer vision, and it is a key step in the applications of 3d reconstruction, object recognition and classification, image alignment and so on. In order to do more precise to the stereo matching of feature points, gave a new matching constraint condition： distance correlation of matching points constraint and proposed a new stereo matching algorithm. The algorithm is independent of feature point detection algorithm, firstly, use the gray correlation method to do ini- tial matching and then use LMedS method to get partial correct matching points set, and on the basis, add distance correlation of matching points constraint to guide the matching. Experiments show that the algorithm can achieve good matches of feature points, and has a very high value

相似文献/References:

[1]黄艳 赵越.3D靶标的摄像机三步标定算法与实现[J].计算机技术与发展,2010,(01):135.
　HUANG Yan,ZHAO Yue.Algorithm and Realization of Three-step Camera Calibration Based on 3D-Target[J].,2010,(03):135.
[2]付海洋 牛连强 刘守琳.一种基于平面模板的单应矩阵求解方法[J].计算机技术与发展,2010,(04):69.
　FU Hai-yang,NIU Lian-qiang,LIU Shou-lin.A Solving Homography Matrix Method Based on Planar Pattern[J].,2010,(03):69.
[3]张铖伟 王彪 徐贵力.摄像机标定方法研究[J].计算机技术与发展,2010,(11):174.
　ZHANG Cheng-wei,WANG Biao,XU Gui-li.A Study on Classification of Camera Calibration Methods[J].,2010,(03):174.
[4]杨晟,李学军,王珏,等.连续尺度复合分析核线重排列影像准稠密匹配[J].计算机技术与发展,2013,(04):111.
　YANG Sheng,LI Xue-jun,WANG Jue,et al.Continuous Scale Multi-change Detecting Quasi-dense Matching for Epipolar Resample Images[J].,2013,(03):111.
[5]卢振宇,郭星,魏赛,等.基于计算机视觉的虚拟安全空间预警技术[J].计算机技术与发展,2014,24(02):237.
　LU Zhen-yu,GUO Xing,WEI Sai,et al.A Surveillance Technology for Virtual Security Space Based on Computer Vision[J].,2014,24(03):237.
[6]李孟,周波,孟正大,等. 三目立体相机的标定研究[J].计算机技术与发展,2015,25(02):69.
　LI Meng,ZHOU Bo,MENG Zheng-da,et al. Study on Trinocular Stereo Camera Calibration[J].,2015,25(03):69.
[7]施泽浩,赵启军.基于全卷积网络的目标检测算法[J].计算机技术与发展,2018,28(05):55.[doi:10.3969/j.issn.1673－629X.2018.05.013]
　SHI Ze-hao,ZHAO Qi-jun.Object Detection Algorithm Based on Fully Convolutional Neural Network[J].,2018,28(03):55.[doi:10.3969/j.issn.1673－629X.2018.05.013]
[8]程龙乐[][],许金林[],李皙茹[][],等. 基于图像处理的跑步机速度自适应技术研究[J].计算机技术与发展,2016,26(10):92.
　CHENG Long-le[][],XU Jin-lin[],LI Xi-ru[][],et al. Research on Speed-adaptive Technology of Treadmill Based on Image Processing[J].,2016,26(03):92.
[9]严一鸣[],郭星[]. 基于计算机视觉的交互式电子沙盘系统研究[J].计算机技术与发展,2017,27(06):195.
　YAN Yi-ming[],GUO Xing[]. Investigation on Interactive Electronic Sand Table System with Computer Vision[J].,2017,27(03):195.
[10]汪 ?涛,成孝刚,李德志,等.基于霍夫变换与角点检测的叶脉特征提取算法[J].计算机技术与发展,2019,29(11):159.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 032]
　WANG Tao,CHENG Xiao-gang,LI De-zhi,et al.A Feature Extraction Algorithm for Leaf Vein Based on Hough Transform and Corner Detection[J].,2019,29(03):159.[doi:10. 3969 / j. issn. 1673-629X. 2019. 11. 032]

备注/Memo

备注/Memo:
福建省自然科学基金资助项目（2009J01294）;宁德师范高等专科学校科研资助项目（2009Y034）毛雁明（1982-），男，福建福安人，硕士研究生，讲师，研究方向为计算机视觉、人工智能
更新日期/Last Update: 1900-01-01