F-SORT: An Alternative for Faster Geometric Verification
F-SORT: An Alternative for Faster Geometric Verification
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F-SORT：更快几何验证的替代方案
DOI：
10.1007/978-3-319-54181-5_25
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
K. Qian
中科院分区：
文献类型：
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作者：
Jacob Chan;J. Lee;K. Qian
本文提出了一种新的几何验证方法-快速序列顺序重新排序技术（F-SORT），能够在任意观看条件下快速验证图像之间的匹配。通过使用一个基本的框架，重新排序图像特征到本地序列组的几何验证沿着不同的方向，我们模拟在各种视图和旋转的每个序列组内的几何约束的执行。虽然传统的几何验证（例如RANSAC）和最先进的完全仿射不变图像匹配方法（例如ASIFT）的计算成本很高，但我们的方法的计算成本要低很多倍。我们评估F-SORT的斯坦福大学移动的视觉搜索（SMVS）和苏黎世建筑物（ZuBuD）的图像数据库，包括一个整体的9个图像类别，并报告相对于PROSAC，RANSAC和ASIFT的竞争力表现。在9个类别中，F-SORT在9个类别中赢得了PROSAC，RANSAC在8个类别中获胜，ASIFT在7个类别中获胜，计算成本分别大幅降低了9倍，30倍和100倍以上。
This paper presents a novel geometric verification approach coined Fast Sequence Order Re-sorting Technique (F-SORT), capable of rapidly validating matches between images under arbitrary viewing conditions. By using a fundamental framework of re-sorting image features into local sequence groups for geometric validation along different orientations, we simulate the enforcement of geometric constraints within each sequence group in various views and rotations. While conventional geometric verification (e.g. RANSAC) and state-of-the-art fully affine invariant image matching approaches (e.g. ASIFT) are high in computational cost, our approach is multiple times less computational expensive. We evaluate F-SORT on the Stanford Mobile Visual Search (SMVS) and the Zurich Buildings (ZuBuD) image databases comprising an overall of 9 image categories, and report competitive performance with respect to PROSAC, RANSAC and ASIFT. Out of the 9 categories, F-SORT wins PROSAC in 9 categories, RANSAC in 8 categories and ASIFT in 7 categories, with a significant reduction in computational cost of over nine-fold, thirty-fold and hundred-fold respectively.
DOI：
10.1007/11744023_32
发表时间：
2006-01-01
期刊：
COMPUTER VISION - ECCV 2006 , PT 1, PROCEEDINGS
影响因子：
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作者：
Bay, Herbert;Tuytelaars, Tinne;Van Gool, Luc
通讯作者：
Van Gool, Luc