首页 | 本学科首页   官方微博 | 高级检索  
     

多视环境下特征点提取的并行实现
引用本文:李文,郭立,袁红星,关华. 多视环境下特征点提取的并行实现[J]. 计算机工程, 2012, 38(1): 182-184
作者姓名:李文  郭立  袁红星  关华
作者单位:中国科学技术大学电子科学与技术系,合肥,230027
基金项目:国家自然科学基金资助项目(61071173); 中国科学技术大学研究生创新基金资助项目
摘    要:针对多视环境下特征点提取计算耗时较长的问题,提出其并行实现方法。通过灰度共生矩阵构造纹理特征差异度,选取关键视点和消除冗余视点,采用Harris角点提取算法、团块检测算法,提取关键视点图像的特征点,利用关键视点选取及特征点提取过程存在的并行性,对算法进行并行实现。实验结果表明,该方法能有效地选取关键视点,在双核处理器上使平均加速比达到1.88。

关 键 词:特征提取  并行算法  多视图像  3D重构  纹理特征
收稿时间:2011-07-26

Parallel Implementation of Characteristic Point Extraction Under Multi-view Environment
LI Wen , GUO Li , JAN Hong-xing , GUAN Hua. Parallel Implementation of Characteristic Point Extraction Under Multi-view Environment[J]. Computer Engineering, 2012, 38(1): 182-184
Authors:LI Wen    GUO Li    JAN Hong-xing    GUAN Hua
Affiliation:(Department of Electronic Science and Technology,University of Science and Technology of China,Hefei 230027,China)
Abstract:Feature extraction in the multi-view environment is an important step in 3D reconstruction.However,it is a very time-consuming task.To accelerate the speed of extracting feature,this paper presents a parallel method to extract feature in the multi-view environment.The key views are selected by the texture feature discrepancy which is computed based on the grey level grows matrix.Harris corner detection algorithm and Blob detection algorithm are adopted to extract feature of the key view images.The method is parallelized by exploring the inherent parallelism of proposed procedures.Experimental results show that the method can select the key views efficiently,and the average speedup achieves 1.88 on a dual-core system.
Keywords:feature extraction  parallel algorithm  multi-view image  3D reconstruction  texture feature
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《计算机工程》浏览原始摘要信息
点击此处可从《计算机工程》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号