期刊文献+

一种仿射不变的直线描述子与直线匹配 被引量:10

An Affine Invariant Line Descriptor and Line Matching
下载PDF
导出
摘要 从图像中提取的直线常出现不完整、端点位置不准确等问题,针对这些问题造成的直线匹配难点,本文提出了一种仿射不变的直线描述子.首先将待匹配直线离散为对应点的集合,将直线描述转化为点的描述,避免了直线不完整造成的支撑区域大小不一致的问题;然后结合直线的方向和长度,定义点描述子的主方向和尺度,通过统计离散点集的局部邻域的梯度信息使描述子具有仿射不变性.为了提高直线匹配速度,在进行直线描述之前,本文采用了极线约束精简了待匹配直线集合,再利用最近邻距离比准则对直线精确匹配.实验结果表明本文提出的直线描述子在仿射、亮度、视点、遮挡等变化条件下具有精确的匹配性能. Line matching is a difficult problem due to reasons such as incomplete lines,inaccurate locations of endpoints,and so on.To deal with these challenges,we proposed an affine invariant line descriptor.An initial candidate match is dispersed to a set of correspondences.As a result,the problem of inconsistent support region size is resolved because we need only construct descriptors of correspondence points instead of lines.In order to make the descriptor affine invariant,the dominant orientation and the scale of the descriptor are created according to the direction and the length of the line,and gradients of the discrete points set in the local neighborhood are calculated.To speed up line matching,epipolar constraint is used before constructing line descriptors,and the number of potential matches is limited.Then,line matching is preceded accurately by the nearest neighbor distance ratio approach.The experimental results show that the proposed descriptor has accurate line matching under the changes of affine,illumination,viewpoint,and partial occlusion.
出处 《电子学报》 EI CAS CSCD 北大核心 2015年第12期2505-2512,共8页 Acta Electronica Sinica
基金 国家自然科学基金(No.61263046 No.61462065) 江西省自然科学基金(No.20122BAB201037)
关键词 直线匹配 直线描述子 仿射不变 极线约束 line matching line descriptor affine invariant epipolar constraint
  • 相关文献

参考文献19

  • 1KOU'IOUDIS A, VIDMAR B, IOANNAKIS G, et al. Multi- image 3D reconstruction data evaluation[ J] .Journal of Cultural Heritage, 2014,15( 1 ) : 73 - 79.
  • 2余烨,刘晓平,Bill P.Buckles.基于数据融合的居民区建筑物重建方法研究[J].电子学报,2014,42(2):250-256. 被引量:4
  • 3HAN J,KIM D,I.EE M, SUNWOO M. Enhanced road bound- ary and obstacle detection using a downward-looking LIDAR sensor[ J]. IEEE Transactions on Vehicular Technology,2012, 61(3) :971 - 985.
  • 4FAN B, WU F C, HU Z Y. Robust line matching through linepoint invariants[ J ]. Pattern Recognition, 2012,45 (2) : 794 - 805.
  • 5LIU Z, MARLET R. Virtual line descriptor and semi-local matching method for reliable feature correspondence[ A ]. Pro- ceedings of British Machine Vision Conference[ C]. Guildford, UK:British Machine Vision Association,2012.1 - 11.
  • 6张云生,朱庆,吴波,邹峥嵘.一种基于三角网约束的立体影像线特征多级匹配方法[J].武汉大学学报(信息科学版),2013,38(5):522-527. 被引量:20
  • 7SCHMID C, ZISSENMAN A. The geometry and matching of lines and curves over multiple views [ J ]. International Journal of Computer Vision, 2000,40(3) : 199 - 233.
  • 8BAY H,FERRARI V,VAN G L.Wide-baseline stereo match- ing with line segments [A]. gs of the lEFt. Computer Society Conference on Computer Vision and Pattern Recogni- tion[ C]. San Diego, USA: 1EEI. Computer Society, 2005. 329 - 336.
  • 9王志衡,吴福朝.均值-标准差描述子与直线匹配[J].模式识别与人工智能,2009,22(1):32-39. 被引量:44
  • 10WANG Z H, WU F C, HU Z Y. MSLD: A robust descriptor for line matching[ J ]. Pattern Recognition, 2009,42 (5) : 941 - 953.

二级参考文献55

  • 1唐亮,谢维信,黄建军,肖志级.城市航空影像中基于模糊Retinex的阴影消除[J].电子学报,2005,33(3):500-503. 被引量:19
  • 2文贡坚.一种基于特征编组的直线立体匹配全局算法[J].软件学报,2006,17(12):2471-2484. 被引量:21
  • 3Tang A W K, Ng T P, Hung Y S, et al. Projective Reconstruction from Line-Correspondences in Multiple Uncalibrated Images. Pattern Recognition, 2006, 39 (5) : 889 - 896
  • 4Aider O A, Hoppenot P, Colle E. A Model-Based Method for Indoor Mobile Robot Localization Using Monocular Vision and Straight-Line Correspondences. Robotics and Autonomous Systems, 2005, 52(2/3 ) : 229 - 246
  • 5Shi Fanhuai, Wang Jianhua, Zhang Jing, et al. Motion Segmentation of Multiple Translation Objects from Line Correspondences. Pat- tern Recognition, 2005, 38(10) : 1775 -1778
  • 6Bartoli A, Sturm P. Multiple-View Structure and Motion from Line Correspondences // Proc of the IEEE International Conference on Computer Vision. Madison, USA, 2003 : 207 -212
  • 7Belongie S, Malik J, Puzicha J. Shape Matching and Object Recognition Using Shape Contexts. IEEE Trans on Pattern Analysis and Machine Intelligence, 2002, 24(4) : 509 -522
  • 8Lowe D G. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 2004, 60 ( 2 ) : 91 -110
  • 9Ke Yan, Sukthankar R. PCA-SIFF: A More Distinctive Representation for Local Image Descriptors// Proc of the IEEE International Conference on Computer Vision and Pattern Recognition. Washington, USA, 2004, II : 506 -513
  • 10Mikolajczyk K, Schmid C. A Performance Evaluation of Local Descriptors. IEEE Trans on Pattern Analysis and Machine Intelligence, 2005, 27 (10) : 1615 - 1630

共引文献57

同被引文献57

引证文献10

二级引证文献35

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部