상세정보
학술지
Robust Uncalibrated Stereo Rectification with Constrained Geometric Distortions (USR-CGD)
- 저자
- 고현석, 심한석, 최욱, C.-C. JayKuo
- 발행일
- 201704
- 출처
- Image and Vision Computing, v.60, pp.98-114
- ISSN
- 0262-8856
- 출판사
- Elsevier
- 협약과제
- 16MR2100, 초고실감 미디어 서비스 실현을 위해 HEVC/3DA 대비 2배 압축을 제공하는 5세대 비디오/오디오 표준 핵심 기술 개발 및 표준화, 김휘용
- 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.
- 키워드
- Constrained optimization, Epipolar geometry, Fundamental matrix, Geometric distortion, Homography, Projective rectification, Regularization
- KSP 제안 키워드
- Adaptive optimization, Balanced performance, Cost Function, Epipolar geometry, Fundamental Matrix, Geometric Distortion, Geometric error, Novel algorithm, Optimization Scheme, Parameter optimization, Projective rectification