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Research Article | Open Access

Homography-guided stereo matching for wide-baseline image interpolation

Peking University, Beijing 100871, China
Beijiing Engineering Technology Research Center of Virtual Simulation and Visualization, Peking University, Beijing 100871, China
The University of Hong Kong, Hong Kong, China
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Abstract

Image interpolation has a wide range of applications such as frame rate-up conversion and free viewpoint TV. Despite significant progresses, it remains an open challenge especially for image pairs with large displacements. In this paper, we first propose a novel optimization algorithm for motion estimation, which combines the advantages of both global optimization and a local parametric transformation model. We perform optimization over dynamic label sets, which are modified after each iteration using the prior of piecewise consistency to avoid local minima. Then we apply it to an image interpolation framework including occlusion handling and intermediate image interpolation. We validate the performance of our algorithm experimentally, and show that our approach achieves state-of-the-art performance.

Keywords

image interpolationview synthesishomo-graphy propagationbelief propagation

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Computational Visual Media
Volume 8 Issue 1,
March 2022
Pages 119-133
DOI: 10.1007/s41095-021-0225-9

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Cite this article:
Chang Y, Zhang C, Chen Y, et al. Homography-guided stereo matching for wide-baseline image interpolation. Computational Visual Media, 2022, 8(1): 119-133. https://doi.org/10.1007/s41095-021-0225-9

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Received: 20 January 2021
Accepted: 14 March 2021
Published: 27 October 2021
© The Author(s) 2021.

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