LI Shouye, HU Maohai, LI Tianran, DUAN Zheyi. Epipolar Rectification Based on Singular Value Decomposition of Camera Translation Matrix[J]. Infrared Technology , 2024, 46(2): 155-161.
Citation: LI Shouye, HU Maohai, LI Tianran, DUAN Zheyi. Epipolar Rectification Based on Singular Value Decomposition of Camera Translation Matrix[J]. Infrared Technology , 2024, 46(2): 155-161.

Epipolar Rectification Based on Singular Value Decomposition of Camera Translation Matrix

More Information
  • Received Date: February 27, 2023
  • Revised Date: March 27, 2023
  • Epipolar rectification is a projection transformation method for the original image pair of a binocular camera such that the corresponding polar lines of the corrected image are on the same horizontal line, no vertical parallax occurs, and stereo-matching is optimized as a one-dimensional search problem. A polar correction method based on a binocular camera translation matrix is proposed to address the shortcomings of current polar correction methods. First, the new corrected rotation matrix is derived using the translation matrix of singular value decomposition. Second, a new camera internal reference matrix is established based on the image relationship before and after correction to complete the polar correction. The proposed method was used to verify multiple groups of binocular images in different scenes in the SYNTIM database. The experimental results show that the average correction error is within 0.6 pixels. The image produces minimal distortion, and the average deviation is approximately 2.4°. The average operation time is 0.2302 s. With its application value, this method fully satisfies polar correction requirements, solves the error, and improves the tedious calculation process caused by the mechanical deviation of the camera during the stereo matching of binocular cameras.
  • [1]
    王学, 周红旭, 张雷, 等. 基于近红外双目立体视觉的悬臂式掘进机定位研究[J/OL]. 工矿自动化: 1-11[2022-09-15]. DOI: 10.13272/j.issn.1671-251x.17896.

    WANG X, ZHOU H X, ZHANG L, et al. Research on cantilever roadheader positioning based on near-infrared binocular stereo vision[J/OL]. [2022-09-15]. Mine Automation, DOI: 10.13272/j.issn.1671-251x.17896.
    [2]
    江荣, 朱攀, 周兴林, 等. 基于双目视觉算法的路面三维纹理信息获取[J]. 激光与光电子学进展, 2022, 59(14): 284-292.

    JIANG R, ZHU P, ZHOU X L, et al. Three-dimensional pavement texture information acquisition based on binocular vision algorithm[J]. Laser & Optoelectronics Progress, 2022, 59(14): 284-292.
    [3]
    舒方林, 张海波, 曹文冠. 基于立体视觉的交叉路口对向车辆运动状态估计[J]. 计算机与数字工程, 2022, 50(5): 1029-1034.

    SHU F L, ZHANG H B, CAO W G. Estimating the motion state of oncoming vehicle based on stereo vision at intersection[J]. Computer & Digital Engineering, 2022, 50(5): 1029-1034.
    [4]
    冉舒文, 刘显明, 雷小华, 等. 基于双目视觉的抬头显示虚像三维形貌测量[J/OL]. [2022-10-26]. 光学学报, http://kns.cnki.net/kcms/detail/31.1252.O4.20220714.1900.522.html.

    RAN S W, LIU X M, LEI X H, et al. Head-up display virtural image 3D topography measurement based on binocular vision[J/OL]. [2022-10-26]. Acta Optica Sinica, http://kns.cnki.net/kcms/detail/31.1252.O4.20220714.1900.522.html
    [5]
    Bouguet J Y. Matlab Camera Calibration Toolbox[EB/OL]. 2000, http://www.vision.caltech.edu\bouguetj\calib_doc.
    [6]
    Andrea Fusiello, Luca Irsara. Quasi-Euclidean epipolar rectification of uncalibrated images[J]. Machine Vision and Applications, 2011, 22(4): 663-670. DOI: 10.1007/s00138-010-0270-3
    [7]
    Richard I Hartley. In defense of the eight-point algorithm[J]. IEEE Trans. Pattern Anal. Mach. Intell., 1997, 19(6): 580-593. DOI: 10.1109/34.601246
    [8]
    Hartley R, Zisserman A. Multiple View Geometry in Computer Vision[M]. Cambridge: Cambridge University Press, 2000.
    [9]
    Richard I Hartley. Theory and practice of projective rectification[J]. International Journal of Computer Vision, 1999, 35(2): 115-127. DOI: 10.1023/A:1008115206617
    [10]
    林国余, 张为公. 一种无需基础矩阵的鲁棒性极线校正算法[J]. 中国图象图形学报, 2006(2): 203-209.

    LIN G Y, ZHANG W G. An Effective robust rectification method for stereo vision[J]. Journal of Image and Graphics, 2006(2): 203-209.
    [11]
    John Mallon, Paul F Whelan. Projective rectification from the fundamental matrix[J]. Image and Vision Computing, 2005, 23(7): 643-650. DOI: 10.1016/j.imavis.2005.03.002
    [12]
    WU Wenhuan, ZHU Hong, ZHANG Qian. Epipolar rectification by singular value decomposition of essential matrix[J]. Multimedia Tools Appl., 2018, 77(12): 15747-15771. DOI: 10.1007/s11042-017-5149-0
    [13]
    Martin A Fischler, Robert C Bolles. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography[J]. Commun. ACM, 1981, 24(6): 381-395. DOI: 10.1145/358669.358692
    [14]
    Hyunsuk Ko, Han Suk Shim, Ouk Choi, et al. Robust uncalibrated stereo Rectification with constrained geometric distortions (USR-CGD)[J]. Image and Vision Computing, 2017, 60: 98-114. DOI: 10.1016/j.imavis.2017.01.001
  • Related Articles

    [1]DING Xiwen, CHENG Hongchang, YUAN Yuan, ZHANG Ruoyu, YANG Shuning, YANG Ye, DANG Xiaogang. Research Status of Local Defect Detection Technology of Ultraviolet Image Intensifier Field of View[J]. Infrared Technology , 2024, 46(2): 129-137.
    [2]LI Yueyi, DING Hongchang, ZHANG Lei, ZHAO Changfu, ZHANG Shibo, WANG Aijia. Pupil Diopter Detection Approach Based on Improved YOLOv3[J]. Infrared Technology , 2022, 44(7): 702-708.
    [3]CAO Yiqing. Design of Double Telecentric Lens Using Machine Vision System[J]. Infrared Technology , 2022, 44(2): 140-144.
    [4]WANG Qianqian, ZHAO Haitao. Depth Estimation of Monocular Infrared Scene Based on Deep CRF Network[J]. Infrared Technology , 2020, 42(6): 580-588.
    [5]WANG Shi'an, WANG Xiangjun, YIN Lei. Accelerative and Weighted Camera Pose Estimation Based on Extended Orthogonal Iterative Algorithm[J]. Infrared Technology , 2020, 42(3): 205-212.
    [6]SONG Daiping, LU Lu. Non-cooperative Circle Characteristic Pose Measurement Using Multiple Cameras without Public Field of View[J]. Infrared Technology , 2020, 42(1): 93-98.
    [7]MIN Zhaoyang, ZHAO Wenjie. Target Anti-Jamming Tracking Algorithm Based on Depth Learning[J]. Infrared Technology , 2018, 40(2): 176-182.
    [8]LI Minqian, CHEN Lin, ZHANG Linghai. Quantitative Identification of Defect Depth by Pulsed Phase[J]. Infrared Technology , 2018, 40(1): 95-98.
    [9]XU qian, Miao Li-feng, WANG Yue-ming, WANG Jian-yu. In-depth Analysis of TDI-CCD Image Senor[J]. Infrared Technology , 2008, 30(12): 683-687. DOI: 10.3969/j.issn.1001-8891.2008.12.001
    [10]CHANG Hong-hua, ZHANG Jian-qi. Machine Vision-Based Quantitative Characterization of IR Background Clutter[J]. Infrared Technology , 2005, 27(5): 403-407. DOI: 10.3969/j.issn.1001-8891.2005.05.013
  • Cited by

    Periodical cited type(1)

    1. 程知,陶寅,邓灶辉,高丽萍,沐超,杜丽丽. 融合残差密集块和对比正则化的单幅图像去雾方法研究. 合肥大学学报. 2025(02): 98-106+122 .

    Other cited types(3)

Catalog

    Article views (115) PDF downloads (20) Cited by(4)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return