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基于ASIFT图像匹配算法的三维重建 被引量:2

Research on Technology of 3-D Reconstruction Based on ASIFT Image Matching Algorithm
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摘要 提出了基于ASIFT图像匹配算法的三维重建算法。目前,基于图像序列的三维重建中,一般采用SIFT图像匹配算法。对于存在仿射变换的图像序列,ASIFT算法较SIFT算法能够获得更多精确的稀疏匹配点;基于ASIFT算法恢复的三维点云比基于SIFT算法恢复的三维点云更加稠密,从而能获得更好的三维重建结果。仿真实验表明,本文算法能获得较好的三维模型。 The algorithm of 3-D reconstruction based on ASIFT image matching algorithm was put forward in this paper. At present, SIFT image matching algorithm is used generally in 3-D reconstruction method based on image sequence. For image sequence existing affine transform, ASIFT image matching algorithm can achieve more quantity and more accurate matches than SIFT image matching algorithm. The recovered 3-D point cloud based on ASIFT image matching algorithm is denser than that based on SIFT image matching algorithm, thus we can get a better 3-D reconstruction results. The simulation experiments show that a better 3-D model can be obtained by our method.
出处 《贵州大学学报(自然科学版)》 2012年第5期72-75,89,共5页 Journal of Guizhou University:Natural Sciences
基金 贵州省优秀教育科技人才省长专项资金项目(200714)
关键词 SIFT ASIFT 图像匹配 三维重建 SIFT ASIFT image matching 3-D reconstruction
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参考文献10

  • 1陈晓霞,陈孝威,刘德宽.基于图像的三维重建流程及实现[J].贵州大学学报(自然科学版),2010,27(4):53-56. 被引量:6
  • 2Mare Pollefey. Visual 3D Modeling from Images[ M ]. North Caroli-n?: University of North C'arolinii,2002.
  • 3徐刚.由2维影像逑立3维模型[M].武汉:武汉大学出版社,2006.
  • 4Lowe D G. Distinctive image features from Scale - Invariant key-points[ J ] . International Journal on Computer Vision, 2004 , 60(2): 91 -110.
  • 5JEAN - MICHKL MOREL, GUOSHEN YU. A new framework forfully affine invariant image r(nnparis(?n[J]. SIAM Journal on Ima-ging Sriences,2009,2(2) :438 -469.
  • 6Marlin A Fischler,Kohert (: Holies. Handom Sampling Conwensus:aparadigm for niocJel lilting with application to image itnaiysis and au-tonmted cartography [ J ].ConmnuiicationK of the ACM , 1981 , 24(6):381 -395.
  • 7J Kosjkova, R Sara. Slratified dense malching for stereopsis incomplex scei?is [ C ]. Harvey, Hit liard , Buii^ham, Andrew. IVo-ceedings of the British Machine Vision Conference . Hrituin : li.VI-VA Press,2003. 33. 1 -33. 10.
  • 8孟晓桥,胡占义.一种新的基于圆环点的摄像机自标定方法[J].软件学报,2002,13(5):957-965. 被引量:51
  • 9K Hartley, A Zissemum. Multiple view geometry in computer vi-sion [ M].2nd edilion. Kiiglaiul : Cambridge University Press,2003?.
  • 10马颂德,张正友.计算机视觉——计算理论算法基础[M].北京:科学出版社,1998.

二级参考文献6

  • 1Lowe D. Distinctive image features from scale - invariant key points[ J]. International Journal on Computer Vision, 2004, 60 (2) : 91 -110.
  • 2Gary Bradski Adrian Kaebler.学习OpenCV(中文版)[M].于仕琪,刘瑞祯译.北京:清华大学出版社,2009:458-463.
  • 3R I Hartley. Estimation of Relative Camera Positions for Unealibrated Cameras [ C ]. In: Proceedings of the Second European Conference on Computer Vision, santa Margherita Ligure : springer - vedag, 1992:579 - 587.
  • 4LHUILLIER M, QUAN L. A quasi - dense approach to surface reconstruction from unealibrated images[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2005, 27(3) : 418 -433.
  • 5邱兆文,张田文.文物三维重建关键技术[J].电子学报,2008,36(12):2423-2427. 被引量:35
  • 6邱建国,张建国,李凯.基于Harris与Sift算法的图像匹配方法[J].测试技术学报,2009,23(3):271-274. 被引量:40

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