Journal
INTERNATIONAL JOURNAL OF COMPUTER VISION
Volume 127, Issue 5, Pages 512-531Publisher
SPRINGER
DOI: 10.1007/s11263-018-1117-z
Keywords
Feature matching; Image registration; Locality preservation; Rigid and non-rigid transformations; Outlier removal
Categories
Funding
- National Natural Science Foundation of China [61773295, 61503288, 61501413, 41501505, 61772512]
- Beijing Advanced Innovation Center for Intelligent Robots and Systems [2016IRS15]
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Seeking reliable correspondences between two feature sets is a fundamental and important task in computer vision. This paper attempts to remove mismatches from given putative image feature correspondences. To achieve the goal, an efficient approach, termed as locality preserving matching (LPM), is designed, the principle of which is to maintain the local neighborhood structures of those potential true matches. We formulate the problem into a mathematical model, and derive a closed-form solution with linearithmic time and linear space complexities. Our method can accomplish the mismatch removal from thousands of putative correspondences in only a few milliseconds. To demonstrate the generality of our strategy for handling image matching problems, extensive experiments on various real image pairs for general feature matching, as well as for point set registration, visual homing and near-duplicate image retrieval are conducted. Compared with other state-of-the-art alternatives, our LPM achieves better or favorably competitive performance in accuracy while intensively cutting time cost by more than two orders of magnitude.
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