cvpr cvpr2013 cvpr2013-102 cvpr2013-102-reference knowledge-graph by maker-knowledge-mining

102 cvpr-2013-Decoding, Calibration and Rectification for Lenselet-Based Plenoptic Cameras


Source: pdf

Author: Donald G. Dansereau, Oscar Pizarro, Stefan B. Williams

Abstract: Plenoptic cameras are gaining attention for their unique light gathering and post-capture processing capabilities. We describe a decoding, calibration and rectification procedurefor lenselet-basedplenoptic cameras appropriatefor a range of computer vision applications. We derive a novel physically based 4D intrinsic matrix relating each recorded pixel to its corresponding ray in 3D space. We further propose a radial distortion model and a practical objective function based on ray reprojection. Our 15-parameter camera model is of much lower dimensionality than camera array models, and more closely represents the physics of lenselet-based cameras. Results include calibration of a commercially available camera using three calibration grid sizes over five datasets. Typical RMS ray reprojection errors are 0.0628, 0.105 and 0.363 mm for 3.61, 7.22 and 35.1 mm calibration grids, respectively. Rectification examples include calibration targets and real-world imagery.


reference text

[1] T. Bishop and P. Favaro. The light field camera: Extended depth of field, aliasing, and superresolution. Pattern Analysis and Machine Intelligence, IEEE Trans. on, 34(5):972–986, May 2012.

[2] L. Condat, B. Forster-Heinlein, and D. Van De Ville. H2O: reversible hexagonal-orthogonal grid conversion by 1-D filtering. In Image Processing, 2007. ICIP 2007. IEEE Intl. Conference on, volume 2, pages II–73. IEEE, 2007.

[3] A. Conn, N. Gould, and P. Toint. Trust region methods, volume 1. Society for Industrial Mathematics, 1987.

[4] D. G. Dansereau, D. L. Bongiorno, O. Pizarro, and S. B. Williams. Light field image denoising using a linear 4D frequency-hyperfan all-in-focus filter. In Proceedings SPIE Computational Imaging XI, page 86570P, Feb 2013.

[5] D. G. Dansereau and L. T. Bruton. A 4-D dual-fan filter bank for depth filtering in light fields. IEEE Trans. on Signal Processing, 55(2):542–549, 2007.

[6] D. G. Dansereau, I. Mahon, O. Pizarro, and S. B. Williams. Plenoptic flow: Closed-form visual odometry for light field cameras. In Intelligent Robots and Systems (IROS), IEEE/RSJIntl. Conf. on, pages 4455–4462. IEEE, Sept 2011.

[7] T. Georgiev, A. Lumsdaine, and S. Goma. Plenoptic principal planes. In Computational Optical Sensing and Imaging. Optical Society of America, 2011.

[8] M. Grossberg and S. Nayar. The raxel imaging model and ray-based calibration. International Journal of Computer Vision, 61(2): 119–137, 2005.

[9] M. Harris. Focusing on everything – light field cameras promise an imaging revolution. IEEE Spectrum, 5:44–50, 2012.

[10] J. Heikkil a¨ and O. Silv e´n. A four-step camera calibration procedure with implicit image correction. In Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, pages 1106–1 112. IEEE, 1997.

[11] A. Kassir and T. Peynot. Reliable automatic camera-laser calibration. In Australasian Conference on Robotics and Automation, 2010.

[12] R. Koch, M. Pollefeys, L. Van Gool, B. Heigl, and H. Niemann. Calibration of hand-held camera sequences for plenoptic modeling. In ICCV, volume 1, pages 585–591 . IEEE, 1999.

[13] D. Lanman. Mask-based Light Field Capture and Display. PhD thesis, Brown University, 2012.

[14] A. Lumsdaine and T. Georgiev. The focused plenoptic camera. In Computational Photography (ICCP), IEEE Intl. Conference on, pages 1–8. IEEE, 2009.

[15] T. Melen. Geometrical modelling and calibration of video cameras for underwater navigation. Institutt for Teknisk Kybernetikk, Universitetet i Trondheim, Norges Tekniske Høgskole, 1994.

[16] R. Ng. Fourier slice photography. In ACM Trans. on Graphics (TOG), volume 24, pages 735–744. ACM, Jul 2005.

[17] R. Ng, M. Levoy, M. Br´ edif, G. Duval, M. Horowitz, and P. Hanrahan. Light field photography with a handheld plenoptic camera. Computer Science Technical Report

[18]

[19]

[20]

[21]

[22]

[23]

[24] CSTR, 2, 2005. T. Svoboda, D. Martinec, and T. Pajdla. A convenient multicamera self-calibration for virtual environments. Presence: Teleoperators & Virtual Environments, 14(4):407– 422, 2005. V. Vaish, M. Levoy, R. Szeliski, C. Zitnick, and S. Kang. Reconstructing occluded surfaces using synthetic apertures: Stereo, focus and robust measures. In Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, volume 2, pages 2331–2338. IEEE, 2006. V. Vaish, B. Wilburn, N. Joshi, and M. Levoy. Using plane + parallax for calibrating dense camera arrays. In Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, volume 1, pages I–2. IEEE, 2004. B. Wilburn, N. Joshi, V. Vaish, E. Talvala, E. Antunez, A. Barth, A. Adams, M. Horowitz, and M. Levoy. High performance imaging using large camera arrays. ACM Trans. on Graphics (TOG), 24(3):765–776, 2005. Z. Xu, J. Ke, and E. Lam. High-resolution lightfield photography using two masks. Optics Express, 20(10): 10971– 10983, 2012. Z. Yu, J. Yu, A. Lumsdaine, and T. Georgiev. An analysis of color demosaicing in plenoptic cameras. In Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, pages 901–908. IEEE, 2012. Z. Zhang. A flexible new technique for camera calibration. Pattern Analysis and Machine Intelligence, IEEE Trans. on, 22(1 1): 1330–1334, 2000. 11111000003333324422