Robust uncalibrated stereo rectification with constrained geometric distortions (USR-CGD)

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초록

A novel algorithm for uncalibrated stereo image-pair rectification under the constraint of geometric distortion, called USR-CGD, is presented in this work. Although it is straightforward to define a rectifying transformation (or homography) given the epipolar geometry, many existing algorithms have unwanted geometric distortions as a side effect. To obtain rectified images with reduced geometric distortions while maintaining a small rectification error, we parameterize the homography by considering the influence of various kinds of geometric distortions. Next, we define several geometric measures and incorporate them into a new cost function as regularization terms for parameter optimization. Finally, we propose a constrained adaptive optimization scheme to allow a balanced performance between the rectification error and the geometric error. Extensive experimental results are provided to demonstrate the superb performance of the proposed USR-CGD method, which outperforms existing algorithms by a significant margin. (C) 2017 Elsevier B.V. All rights reserved.

키워드

Projective rectificationRegularizationHomographyEpipolar geometryFundamental matrixGeometric distortionConstrained optimizationPROJECTIVE RECTIFICATIONVISION
제목
Robust uncalibrated stereo rectification with constrained geometric distortions (USR-CGD)
저자
Ko, HyunsukShim, Han SukChoi, OukKuo, C. -C. Jay
DOI
10.1016/j.imavis.2017.01.001
발행일
2017-04
유형
Article
저널명
Image and Vision Computing
60
페이지
98 ~ 114