基于鱼眼相机的立体图像校正和图像拼接
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摘要
双目立体视觉一直是计算机视觉领域的研究热点。由于传统透视相机的视野范围大小的局限性,具有宽广视野的超广角相机在计算机视觉领域的应用受到了人们越来越多的关注。超广角相机图像的拼接,大大减少了所需图像序,列的数目,具有很好的应用前景。
本文主要研究基于鱼眼相机的立体视觉相关算法及其基于鱼眼相机的图像拼接。本文的主要内容包括：
提出了一种基于泰勒级数模型的鱼眼相机立体视觉方法。利用泰勒级数模型对立体视觉相机进行标定,推导了泰勒级数模型到理想透视投影模型的映射关系,将鱼眼图像去失真展开为理想的透视投影图像,同时也获得了虚拟透视相机的摄像机内参。利用平面模板标定出立体视觉相机间的外参数,对立体图对进行外极线校正。根据相机的投影模型推导了鱼眼立体相机的深度信息恢复方法,完成三维重建。
以汽车周身监视系统为应用背景,研究了一种基于泰勒级数模型的鱼眼图像拼接。将四幅两两交叠的鱼眼图像进行去失真处理,投影到一个共同平面,得到合成的虚拟视点下的鸟瞰图像。
Binocular stereo vision is research hot spot in computer vision. Due to the limitation of the field of view of the perspective camera, the application of large field of view camera with wide angle lens in computer vision draws more and more attention. Due to sharp decrease in the number of images, image stitching based on images captured by large angle camera has a good application prospect.
This thesis is mainly about stereo vision algorithms and image stitching based on fisheye camera.
We proposed fisheye stereo based on the Taylor model firstly. The Taylor series model is used to calibrate the stereo camera. Based on this model, the mapping relationship between perspective model and Taylor model is obtained, which can be used to undistort the fisheye image. The interior parameters of the virtual perspective camera can be set directly. The exterior parameters of the binocular cameras calibrated by using calibration pattern are used in epipolar rectification of the stereo image pair. Derivation of the depth information of stereo pair is also performed before 3D reconstruction.
Image Stitching based on Taylor model is researched aimed to the application of vehicle surrounding monitoring. Four overlapped fisheye images are undistorted into perspective ones. Then we projected them into one common plane and fused them into one monitoring image.
本文主要研究基于鱼眼相机的立体视觉相关算法及其基于鱼眼相机的图像拼接。本文的主要内容包括：
提出了一种基于泰勒级数模型的鱼眼相机立体视觉方法。利用泰勒级数模型对立体视觉相机进行标定,推导了泰勒级数模型到理想透视投影模型的映射关系,将鱼眼图像去失真展开为理想的透视投影图像,同时也获得了虚拟透视相机的摄像机内参。利用平面模板标定出立体视觉相机间的外参数,对立体图对进行外极线校正。根据相机的投影模型推导了鱼眼立体相机的深度信息恢复方法,完成三维重建。
以汽车周身监视系统为应用背景,研究了一种基于泰勒级数模型的鱼眼图像拼接。将四幅两两交叠的鱼眼图像进行去失真处理,投影到一个共同平面,得到合成的虚拟视点下的鸟瞰图像。
Binocular stereo vision is research hot spot in computer vision. Due to the limitation of the field of view of the perspective camera, the application of large field of view camera with wide angle lens in computer vision draws more and more attention. Due to sharp decrease in the number of images, image stitching based on images captured by large angle camera has a good application prospect.
This thesis is mainly about stereo vision algorithms and image stitching based on fisheye camera.
We proposed fisheye stereo based on the Taylor model firstly. The Taylor series model is used to calibrate the stereo camera. Based on this model, the mapping relationship between perspective model and Taylor model is obtained, which can be used to undistort the fisheye image. The interior parameters of the virtual perspective camera can be set directly. The exterior parameters of the binocular cameras calibrated by using calibration pattern are used in epipolar rectification of the stereo image pair. Derivation of the depth information of stereo pair is also performed before 3D reconstruction.
Image Stitching based on Taylor model is researched aimed to the application of vehicle surrounding monitoring. Four overlapped fisheye images are undistorted into perspective ones. Then we projected them into one common plane and fused them into one monitoring image.
引文
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[2]C. Peng and M. Hebert, "Omni-directional structure from motion," in Omnidirectional Vision,2000. Proceedings. IEEE Workshop on,2000, pp.127-133.
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[4]L. Shigang, "Real-Time Spherical Stereo," in Pattern Recognition,2006. ICPR 2006. 18th International Conference on,2006, pp.1046-1049.
[5]S. Li, "Binocular Spherical Stereo," Intelligent Transportation Systems, IEEE Transactions on, vol.9, pp.589-600,2008.
[6]S. Abraham and W. Forstner, "Fish-eye-stereo calibration and epipolar rectification," ISPRS Journal of photogrammetry and remote sensing, vol.59, pp.278-288,2005.
[7]J. Heller and T. Pajdla, "Stereographic rectification of omnidirectional stereo pairs," in Computer Vision and Pattern Recognition,2009. CVPR 2009. IEEE Conference on, 2009, pp.1414-1421.
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[11]L. Shigang, "Monitoring Around a Vehicle by a Spherical Image Sensor," Intelligent Transportation Systems, IEEE Transactions on, vol.7, pp.541-550,2006.
[12]Y.-C. Liu, K.-Y. Lin, and Y.-S. Chen, "Bird's-Eye View Vision System for Vehicle Surrounding Monitoring," in Robot Vision,2008, pp.207-218.
[13]D. Scaramuzza, A. Martinelli, and R. Siegwart, "A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion," in Computer Vision Systems,2006 ICVS'06. IEEE International Conference on,2006, pp.45-45.
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[15]J. Maki, J. Bell III, K. Herkenhoff, S. Squyres, A. Kiely, M. Klimesh, M. Schwochert, T. Litwin, R. Willson, and A. Johnson, "Mars exploration rover engineering cameras," Journal of Geophysical research, vol.108, pp.12-1,2003.
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[24]D. Schneider, E. Schwalbe, and H. Maas, "Validation of geometric models for fisheye lenses," ISPRS Journal of photogrammetry and remote sensing, vol.64, pp.259-266, 2009.
[25]J. Kannala and S. S. Brandt, "A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.28, pp.1335-1340,2006.
[26]英向华,胡占义,”一种基于球面透视投影约束的鱼眼镜头校正方法,”计算机学报vol.26,pp.1702-1708,2003.
[27]J. Gluckman and S. K. Nayar, "Rectified catadioptric stereo sensors," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.24, pp.224-236,2002.
[28]W. L. D. Lui and R. Jarvis, "Eye-Full Tower: A GPU-based variable multibaseline omnidirectional stereovision system with automatic baseline selection for outdoor mobile robot navigation," Robotics and Autonomous Systems, vol.58, pp. 747-761, 2010.
[29]S. Liancheng and Z. Feng, "Design of a novel stereo vision navigation system for mobile robots," in Robotics and Biomimetics (ROBIO).2005 IEEE International Conference on, 2005, pp.611-614.
[30]S. Gehrig, C. Rabe, and L. Krueger, "6D Vision Goes Fisheye for Intersection Assistance," in Computer and Robot Vision,2008. CRV'08. Canadian Conference on, 2008, pp.34-41.
[31]C. Geyer and K. Daniilidis, "Conformal Rectification of Omnidirectional Stereo Pairs," in Computer Vision and Pattern Recognition Workshop,2003. CVPRW'03. Conference on,2003, pp.73-73.
[32]Z. Arican and P. Frossard, "Dense disparity estimation from omnidirectional images," in Advanced Video and Signal Based Surveillance,2007. AVSS 2007. IEEE Conference on, 2007, pp.399-404.
[33]W. Dingrui, Z. Jie, and D. Zhang, "A Spherical Rectification for Dual-PTZ-Camera System," in Acoustics, Speech and Signal Processing,2007. ICASSP 2007. IEEE International Conference on,2007, pp. I-777-I-780.
[34]S. Cagnoni, M. Mordonini, L. Mussi, and G. Adorni, "Spherical rectification based stereo vision applied to hybrid dual camera vision systems," in Workshop on Omnidirectional Robot Vision (SIMPAR),2008.
[35]杜歆,徐钢梅,朱云芳,王贻术,“一种基于单相机三维重建的简单方法,”传感技术学报vol.20,pp.1917-1920,2007.
[36]A. Klaus, M. Sormann, and K. Karner, "Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure," in Pattern Recognition,2006. ICPR 2006.18th International Conference on,2006, pp.15-18.
[37]M. Z. Brown, D. Burschka, and G. D. Hager, "Advances in computational stereo," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.25, pp.993-1008, 2003.
[38]F. Schaffalitzky and A. Zisserman, "Viewpoint invariant texture matching and wide baseline stereo," in Computer Vision,2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on,2001, pp.636-643 vol.2.
[39]C. Schmid and A. Zisserman, "The Geometry and Matching of Lines and Curves Over Multiple Views," International Journal of Computer Vision, vol.40, pp.199-233,2000.
[40]B. J. Super and W. N. Klarquist, "Patch-based stereo in a general binocular viewing geometry," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.19, pp.247-253,1997.
[41]B. Lucas and T. Kanade, "An iterative image registration technique with an application to stereo vision," 1981, pp.674-679.
[42]V. Venkateswar and R. Chellappa, "Hierarchical stereo and motion correspondence using feature groupings," International Journal of Computer Vision, vol.15, pp.245-269, 1995.
[43]M. Bleyer and M. Gelautz, "A layered stereo matching algorithm using image segmentation and global visibility constraints," ISPRS Journal of photogrammetry and remote sensing, vol.59, pp.128-150,2005.
[44]H. Li and G. Chen, "Segment-based stereo matching using graph cuts," in Computer Vision and Pattern Recognition,2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on,2004, pp. I-74-I-81 Vol.1.
[45]C. Zitnick, "High-quality Video View Interpolation Using a Layered Representation," ACM transactions on graphics, p.598,2004.
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