Two-frame wide baseline matching

Jiangjian Xiao, M. Shah
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引用次数: 95

Abstract

We describe a novel approach to automatically recover corresponding feature points and epipolar geometry over two wide baseline frames. Our contributions consist of several aspects: First, the use of an affine invariant feature, edge-corner, is introduced to provide a robust and consistent matching primitives. Second, based on SVD decomposition of affine matrix, the affine matching space between two corners can be approximately divided into two independent spaces by rotation angle and scaling factor. Employing this property, a two-stage affine matching algorithm is designed to obtain robust matches over two frames. Third, using the epipolar geometry estimated by these matches, more corresponding feature points are determined. Based on these robust correspondences, the fundamental matrix is refined, and a series of virtual views of the scene are synthesized. Finally, several experiments are presented to illustrate that a number of robust correspondences can be stably determined for two wide baseline images under significant camera motions with illumination changes, occlusions, and self-similarities. After testing a number of examples and comparing with the existing methods, the experimental results strongly demonstrate that our matching method outperforms the state-of-art algorithms for all of the test cases.
两帧宽基线匹配
我们描述了一种在两个宽基线框架上自动恢复相应特征点和极几何的新方法。我们的贡献包括以下几个方面:首先,引入了仿射不变特征边角的使用,以提供鲁棒和一致的匹配原语。其次,基于仿射矩阵的SVD分解,通过旋转角度和比例因子将两个角间的仿射匹配空间近似划分为两个独立的空间;利用这一特性,设计了一种两阶段仿射匹配算法,以获得两帧的鲁棒匹配。第三,利用这些匹配估计的极面几何,确定更多对应的特征点。基于这些鲁棒性对应关系,对基本矩阵进行了细化,并合成了一系列场景的虚拟视图。最后,几个实验提出,以说明一些鲁棒对应可以稳定地确定两个宽基线图像在显著的相机运动与照明变化,遮挡和自相似性。经过大量的实例测试和与现有方法的比较,实验结果表明,我们的匹配方法在所有测试用例中都优于当前的匹配算法。
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