Motion Statistic Based Local Homography Transformation Estimation for Mismatch Removal
Pages 47 - 50
Abstract
Accurately establishing pixel-level correspondence between images taken from same objects is an essential problem in many computer vision applications, such as 3D reconstruction, simultaneous localization and mapping (SLAM), and augmented reality (AR). Existing local feature descriptor based image matching approaches are unable to avoid mismatches which cause negative effects to the above mentioned applications. This paper proposes a motion statistic based local homography transformation estimation method for removing mismatches. The proposed method estimates local homography transformations between the grids in a pair of images and then classifies each match as correct or incorrect by checking whether it is consisting with the corresponding local homography transformation or not. Experimental results on the widely used Oxford affine image dataset show that the proposed approach finds out more potential correct matches than the existing state-of-the-art method.
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Index Terms
- Motion Statistic Based Local Homography Transformation Estimation for Mismatch Removal
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Published In
July 2019
80 pages
ISBN:9781450371612
DOI:10.1145/3348488
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- Nanyang Technological University
- University of Tsukuba: University of Tsukuba
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 27 July 2019
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AIVR 2019
AIVR 2019: 2019 3rd International Conference on Artificial Intelligence and Virtual Reality
July 27 - 29, 2019
Singapore, Singapore
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