CASIA OpenIR  > 毕业生  > 硕士学位论文
Alternative TitleMatching between Omnidirectional and Perspective Images, and 3D Reconstruction
Thesis Advisor吴毅红
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword几何不变量 图像匹配扩散 多模型摄像机 三维重建 立体视觉 Geometric Invariant Image Matching Multi-modal Cameras 3d Reconstruction Stereovision
Abstract全向摄像机与透视摄像机的混合视觉系统可以发挥各自摄像机的优势而弥补各自的不足,如全向摄像机可以增大视野,透视摄像机的信息可以用来补偿全向摄像机成像的分辨率不足。在计算机视觉领域不同图像之间对应点的确定,即图像匹配,是一个基本问题。国内外在透视图像匹配领域已经有很多比较成熟的算法,但全向图像之间或全向图像与透视图像之间的匹配算法还很少。由于全向图像有着严重的畸变,关于它的匹配研究有着一定的困难。 本文主要是对全向与透视图像进行特征点匹配并将匹配算法应用于计算机视觉的一些具体问题,所完成的主要工作有: ² 推导出了全向图像和透视图像间的几何不变量。该几何不变量是根据一个射影几何不变量(交比)以及线束和面束交比性质推导的,可用于图像匹配的几何约束和摄像机标定。 ² 将建立的全向图像与透视图像间的几何不变量应用于图像匹配,提出了一个全向与透视图像准稠密匹配算法,其中场景由平面组成,该算法不需要事先标定摄像机,也不需要对全向图像矫正。首先用宽基线透视图像匹配算法找出全向与透视图像对的初始匹配作为种子点,然后用线性变换确定候选对应点所在的区域,接着计算几何不变量作为准稠密匹配的几何约束,最后将计算出的几何不变量结合Lhuillier 和Quan(2002)的最优最先策略,准稠密对应点即可计算出。真实数据的实验表明,该算法能够得到分布均匀的准稠密匹配点,能满足三维重建的要求。 ² 将提出的全向与透视图像准稠密匹配算法应用于三维重建。首先在除式模型下,利用几何不变量和已有的匹配点计算出全向摄像机的内参数K,然后通过解经典的P3P 问题求得外参数R,t。接着应用张正友平面标定方法计算出透视摄像机的内外参数。两个摄像机标定好后,不但可以求得两摄像机的相对位置,也可以用三角化方法重建出场景的三维模型,实验中获得了良好的三维重建效果。
Other AbstractA kind of vision sensors consisting of an omnidirectional camera and a perspective camera is greatly useful. The omnidirectional camera can be used to monitor surroundings with wide-angle field of view and the perspective camera can be used to gaze at interest objects with high resolution. Image matching underlies many problems in computer vision. Many fairly mature image matching algorithms between perspective images have been proposed. However, because omnidirectional cameras have severe distortions, these previous image matching algorithms cannot be used for omnidirectional images directly. Researches on image matching involving omnidirectional images are still very few. In this dissertation, the main work is focused on the image matching between omnidirectional and perspective images, as well as their applications. The summary is as follows: ² A geometric invariant equation between omnidirectional and perspective images of the same scene consisting of planes is presented. This equation is based on cross ratios of pencils of lines and planes. It could be used to be a geometric constraint during image match propagation and to calibrate omnidirectional cameras. ² Based on the above derived invariant equation between omnidirectional and perspective images, a quasi-dense matching algorithm between such a pair of images is proposed. This algorithm does not require a camera calibration or a rectification for the omnidirectional image. First, the image matching algorithm between conventional wide baseline perspective images is used to obtain the initial matches between omnidirectional and perspective images. Second, a linear transformation is introduced to identify the area containing the corresponding point candidates. Then, the geometric invariant equation is computed as a constraint for quasi-dense matching. Finally, combining the computed geometric invariant with a best-first strategy of Lhuillier and Quan (2002), the quasi-dense point correspondences are calculated. The experiments with real data show that this algorithm could obtain quasi-dense point correspondences with even distribution which can satisfy the requirement of 3D reconstruction. ² The quasi-dense point correspondences obtained above are applied to 3D reconstruction. First, the geometric invariant equation and the computed point correspondences are used to calibrate the intrinsic parameters K of the omnidirectional camera under the division model of radial distortion. The...
Other Identifier200628014628040
Document Type学位论文
Recommended Citation
GB/T 7714
陆玲玲. 全向与透视图像匹配及三维重建[D]. 中国科学院自动化研究所. 中国科学院研究生院,2009.
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