Geometric Verification Method of Best Score Increasing Subsequence for Object Instance Recognition

Gede Putra Kusuma, Kristopher David Harjono, Muhammad Taufik Dwi Putra
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引用次数: 1

Abstract

Weighted Longest Increasing Subsequence (WLIS) and its improvement, Best Increasing Subsequence (BIS) are two methods that has been proposed for pair verification in object instance recognition using local features. Tested on the Stanford Mobile Visual Dataset (SMVS), the BIS achieves better performance than WLIS on most categories, except for the “video frames” category. In this paper we propose several modifications to BIS which resulted in a better overall performance compared to the WLIS and the basic BIS approaches. On average, the proposed Best Score Increasing Subsequence (BSIS) performs 4.53% better than the BIS and 9.43% better than the WLIS.
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目标实例识别的最佳分数递增子序列几何验证方法
加权最长递增子序列(WLIS)及其改进的最佳递增子序列(BIS)是利用局部特征对目标实例识别进行对验证的两种方法。在斯坦福移动视觉数据集(SMVS)上测试,BIS在大多数类别上都比WLIS表现更好,除了“视频帧”类别。在本文中,我们提出了对BIS的一些修改,与WLIS和基本BIS方法相比,这些修改导致了更好的整体性能。平均而言,所提出的最佳分数增加子序列(BSIS)比BIS好4.53%,比WLIS好9.43%。
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