Journal of Computer Applications ›› 2013, Vol. 33 ›› Issue (03): 635-639.DOI: 10.3724/SP.J.1087.2013.00635

• Network and distributed techno • Previous Articles     Next Articles

Wide baseline image matching for 3D objects

LI Wei1,2,3*, SHI Zelin1,2, YIN Jian4   

  1. 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang Liaoning 110016, China;
    2.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang Liaoning 110016, China;
    3.School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China;
    4.Research Institute on General Development and Argumentation of Equipment of Air Force, Beijing 100076, China
  • Received:2012-09-11 Revised:2012-10-09 Online:2013-03-01 Published:2013-03-01
  • Contact: LI WEI

立体目标的宽基线图像匹配

李威1,2,3*,史泽林1,2,尹健4   

  1. 1.中国科学院 沈阳自动化研究所,沈阳 110016;
    2.中国科学院 光电信息处理重点实验室,沈阳 110016; 3.中国科学院大学 计算机与控制学院,北京 100049;
    4.空军装备研究院总体所,北京 100076
  • 通讯作者: 李威
  • 作者简介:李威(1982-),男,河南唐河人,博士研究生,主要研究方向:自动目标识别与跟踪; 史泽林(1965-),男,江苏宜兴人,研究员,博士生导师,主要研究方向:光电成像、光电跟踪、图像处理、目标识别。
  • 基金资助:

    国家973计划项目; 中国科学院国防科技创新基金资助项目(CXJJ-11)。

Abstract: An affine invariant local feature detector has been put forward for 3D object image matching. In order to cope with view angle and scale changes, this algorithm changed the image structure to fit the circular Gaussian filter according to the principle that Gaussian filter and image structure should be compatible. Local image structures were measured by covariance matrixes of Maximally Stable Extremal Regions (MSER) having been detected in the image. Anisotropic image structures must be rotated and squeezed into isotropic image structures to guarantee the correctness of image transformation. Finally, Scale Invariant Feature Transform (SIFT) features were extracted on isotropic image structures. Coordinates of SIFT features should be changed into the original image coordinates after being extracted. The experimental results indicate that the local features extracted by this algorithm are fully affine invariant. They are suitable to be used in wide baseline image matching for 3D objects.

Key words: 3D object image matching, wide baseline, affine invariant, local feature extraction, anisotropic

摘要: 为了匹配立体目标的图像特征,提出一种仿射不变的局部特征提取算法。根据高斯滤波器的形状和大小要与图像结构相适应的原理,该算法利用图像中的最大稳定极值区域(MSER)的协方差矩阵衡量局部图像结构,并将局部图像结构变换到圆形高斯滤波器适用的形式下,以解决视角和尺度变化问题。为了保证图像变换的正确性,采用旋转压缩的方式将各向异性的图像结构变换为各向同性的图像结构。最后在各向同性的图像结构上提取尺度不变特征变换(SIFT)特征点,并将SIFT特征点的坐标变回原图像坐标。实验结果表明该算法提取的局部特征是完全仿射不变的,在立体目标的宽基线图像匹配中表现出良好的效果。

关键词: 立体目标图像匹配, 宽基线, 仿射不变, 局部特征提取, 各向异性

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