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Alternative TitleA Study On Image Match Propagation
Thesis Advisor胡占义 ; 孙凤梅
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准稠密匹配 扩散 鱼眼图像 仿射变换 邻域传递 Quasi-dense Matching Propagation Fish-eye Image Affine Transform Neighborhood-transfer
Abstract三维重建,即从二维图像恢复三维物体可见表面的几何结构的过程,一直是计算机视觉的重要研究内容。近年来,随着三维重建在数字地球、数字考古、数字娱乐等领域应用的不断发展,物体表面结构的视觉效果已成为三维重建越来越关注的一个问题。然而要得到逼真视觉效果,就需要稠密至少是准稠密的比较精确的图像点匹配。当前比较流行的特征匹配方法只能得到比较稀疏的匹配点对,用这些稀疏的点对一般很难重建恢复三维物体的完整形状。稀疏匹配点一般比较适宜于估计极几何关系和确定相机参数。对短基线下的立体图像对的稠密匹配文献中有很多研究,但计算量非常大。而匹配的扩散策略在匹配数量、精度和计算时间之间一般能达到一个较好的平衡。 本文主要围绕如何用扩散的方法得到准稠密匹配这一问题展开研究。主要工作有以下几个方面: · 针对三维重建需要比较稠密的匹配以提高重建效果的要求,改进并实现了一种基于透视图像对的匹配扩散算法。在文中重点讨论了种子匹配的获取方法以及匹配的扩散策略。此算法能得到分布均匀、精度较高的准稠密匹配。对于应用中的一些问题,本文还给出了关于其解决方法的讨论以及相关实现。 · 针对鱼眼图像高畸变的特点,提出了一种适合于鱼眼图像的准稠密匹配扩散算法。该算法采用局部仿射模型来建立图像对应区域之间的变换关系,并利用这个仿射变换来规范化对应区域,最后在规范化的区域上进行匹配扩散。在局部仿射变换的计算中,采用邻域传递的思路,边扩散边邻域更新,使扩散始终在较准确的对应区域内进行。实验表明,在大畸变的鱼眼图像下,文中提出的准稠密扩散算法仍能取得比较令人满意的匹配结果。 · 统一了透视图像对、鱼眼图像对的匹配扩散算法,给出了一个统一的扩散框架模型,使其适用于各种图像之间点匹配和区域匹配的扩散。在此基础之上,进一步深入探讨了种子匹配对应邻域的选择、扩散得到的匹配的分布调整、精定位、可控性以及遮挡与边界的处理等扩散相关问题,并给出了相应的解决方法与相关思考。最后还讨论了多幅图像之间的匹配扩散问题。
Other Abstract3D reconstruction, i.e. to recover scenes’ visible surfaces from images, has been the fundamental problem in computer vision. Recently, reconstructions are increasingly used on applications such as digital earth, digital archaeology and digital entertainment, where the visual quality of reconstructed scenes rather than the strict shape, becomes the major concern. The high quality visual effect needs dense or at least quasi-dense matches, who cannot be obtained by currently popular feature extracting and matching approaches, for they can only find sparse correspondences, and sparse correspondences are more suitable for estimating epipolar geometry and camera parameters. Dense stereo matching has been studied more thoroughly and can produce promising results, but is much more costly at the same time. Moreover, stereo matching methods often require strict camera configuration. On contrast, match propagation, a promising strategy, can make a good balance between these two aspects. In this dissertation, the main work is focused on how to find quasi-dense matches through match propagation, i.e. how to propagate matches from some sparse matches to their neighborhoods. The main work is 3-fold: · In order to meet the needs of reconstruction, an improved match propagation algorithm for perspective images is proposed, implemented and tested. The issues of getting precise seed matches and propagation strategy are thoroughly discussed. The algorithm can produce not only well-distributed but also accurate matches. In addition, some practical issues in real applications are also discussed. · A novel quasi-dense matching algorithm through local neighborhood transfer is proposed for fish-eye images, characterized by severe projective distortions. A local affine model is used for the geometric transformation between two corresponding image patches. Patches are normalized with the known affine transformation before match propagation is applied to them. The local affine transformation is computed during the propagation by a new mechanism, called neighborhood-transfer, to ensure the propagation be carried out in the correct neighborhood. Experiments with real fish-eye images show that our algorithm can provide satisfactory results. · A unified framework is proposed which could accommodate match propagation between different kinds of images, including perspective images, fish-eye images and catadioptric images. This unified framework is applicable for both po...
Other Identifier200628014628059
Document Type学位论文
Recommended Citation
GB/T 7714
许振辉. 图像的匹配扩散研究[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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