Camera array calibration for light field acquisition

Abstract

Light field cameras are becoming popular in computer vision and graphics, with many research and commercial applications already having been proposed.Various types of cameras have been developed with the camera array being one of the ways of acquiring a 4D light field image usingmultiple cameras. Camera calibration is essential, since each application requires the correct projection and ray geometry of the light field. The calibrated parameters are used in the light field image rectified from the images captured by multiple cameras. Various camera calibration approaches have been proposed for a single camera, multiple cameras, and amoving camera. However, although these approaches can be applied to calibrating camera arrays, they are not effective in terms of accuracy and computational cost. Moreover, less attention has been paid to camera calibration of a light field camera. In this paper, we propose a calibration method for a camera array and a rectification method for generating a light field image from the captured images. We propose a two-step algorithm consisting of closed form initialization and nonlinear refinement, which extends Zhang’swell-known method to the camera array. More importantly, we introduce a rigid camera constraint whereby the array of cameras is rigidly aligned in the camera array and utilize this constraint in our calibration. Using this constraint, we obtained much faster and more accurate calibration results in the experiments.

Keywords

light field / camera array / calibration / rectification / digital refocusing

References

[1] Levoy M, Hanrahan P. Light field rendering. In: Proceedings of the ACM Conference on Computer Graphics. 1996, 31―42

[2] Ng R, Levoy M, Brédif M, Duval G, Horowitz M, Hanrahan P. Light Field Photography with a Hand-Held Plenoptic Camera. Computer Science Technical Report CSTR, 2005

[3] Vaish V, Levoy M, Szeliski R, Zitnick C L, Kang S B. Reconstructing occluded surfaces using synthetic apertures: stereo, focus and robust measures. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2006, 2331―2338

[4] Seitz S M, Curless B, Diebel J, Scharstein D, Szeliski R S. A comparison and evaluation of multi-view stereo reconstruction algorithms. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2006, 519―528

[5] Wetzstein G, Roodnick D, Heidrich W, Raskar R. Refractive shape from light field distortion. In: Proceedings of IEEE International Conference on Computer Vision. 2011, 1180―1186

[6] Maeno K, Nagahara H, Shimada A, Taniguchi R. Light field distortion feature for transparent object recognition. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013, 2786―2793

[7] Wilburn B, Joshi N, Vaish V, Talvala E V E, Antunez E, Barth A, Adams A, Levoy M, Horowitz M. High performance imaging using large camera arrays. ACM Transactions on Graphics, 2005, 24(3): 765―776

[8] Zhang Z. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11): 1330―1334

[9] Ueshiba T, Tomita F. Plane-based calibration algorithm for multicamera systems via factorization of homography matrices. In: Proceedings of IEEE International Conference on Computer Vision. 2003, 966―973

[10] Snavely N, Seitz S M, Szeliski R. Modeling the world from internet photo collections. International Journal of Computer Vision, 2008, 80: 189―210

[11] Bok Y, Jeon H G, Kweon I S. Geometric calibration of micro-lensbased light-field cameras using line features. In: Proceedings of European Conference on Computer Vision. 2014, 8694: 47―61

[12] Dansereau D G, Pizarro O, Williams S B. Decoding, calibration and rectification for lenselet-based plenoptic cameras. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2013, 1027―1034

[13] Cho D, Lee M, Kim S, Tai Y W. Modeling the calibration pipeline of the lytro camera for high quality light-field image reconstruction. In: Proceedings of IEEE International Conference on Computer Vision. 2013

[14] Tsai R Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses. IEEE Journal of Robotics and Automation, 1987, 3: 323―344

[15] Vaish V, Wilburn B, Joshi N, Levoy M. Using plane+ parallax for calibrating dense camera arrays. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (1). 2004, 2―9

[16] Svoboda T, Martinec D, Pajdla T. A convenient multi-camera selfcalibration for virtual environments. PRESENCE: Teleoperators and Virtual Environments, 2005, 14(4): 407―422

[17] Loop C, Zhang Z. Computing rectifying homographies for stereo vision. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1999, 125―131

[18] Fusiello A, Trucco E, Verri A. A compact algorithm for rectification of stereo pairs. Machine Vision and Applications, 2000, 12(1): 16―22

[19] Deng K, Wang L, Lin Z, Feng T, Deng Z. Correction and rectification of light fields. Computers & Graphics, 2003, 27(2): 169―177

[20] Fukushima N, Yendo T, Fujii T, Tanimoto M. A novel rectification method for two-dimensional camera array by parallelizing locus of feature points. In: Proceedings of International Workshop on Advanced Image Technology. 2008, B5―1

[21] Heikkila J, Silven O. A four-step camera calibration procedure with implicit image correction. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1997, 1106―1112

[22] Wei G Q, Ma S D. Implicit and explicit camera calibration: Theory and experiments. IEEE Transactions of Pattern Analysis and Machine Intelligence, 1994, 16(5): 469―480

[23] Levenberg K. A method for the solution of certain non-linear problems in least squares. Quarterly Journal of Applied Mathmatics, 1944, II(2): 164―168

[24] Marquardt D W. An algorithm for least-squares estimation of nonlinear parameters. SIAM Journal on Applied Mathematics, 1963, 11(2): 431―441

[25] Ihm I, Park S, Lee R K. Rendering of spherical light fields. In: Proceedings of the 5th Pacific Conference On Computer Graphics And Applications. 1997, 59―68

[26] Georgiev T, Lumsdaine A. Focused plenoptic camera and rendering. Journal of Electronic Imaging, 2010, 19(2)

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Higher Education Press and Springer-Verlag Berlin Heidelberg