Abstract
The ability of light gathering of plenoptic camera opens up new opportunities for a wide range of computer vision applications. An efficient and accurate method to calibrate plenoptic camera is crucial for its development. This paper describes a 10-intrinsic-parameter model for focused plenoptic camera with misalignment. By exploiting the relationship between the raw image features and the depth–scale information in the scene, we propose to estimate the intrinsic parameters from raw images directly, with a parallel biplanar board which provides depth prior. The proposed method enables an accurate decoding of light field on both angular and positional information, and guarantees a unique solution for the 10 intrinsic parameters in geometry. Experiments on both simulation and real scene data validate the performance of the proposed calibration method.
Article PDF
Similar content being viewed by others
References
Ng, R. Digital light field photography. Ph.D. Thesis. Stanford University, 2006.
Ng, R.; Levoy, M.; Bredif, M.; Duval, G.; Horowitz, M.; Hanrahan, P. Light field photography with a handheld plenoptic camera. Stanford University Computer Science Tech Report CSTR 2005-02, 2005.
Georgiev, T. G.; Lumsdaine, A. Focused plenoptic camera and rendering. Journal of Electronic Imaging Vol. 19, No. 2, 021106, 2010.
Lumsdaine, A.; Georgiev, T. Full resolution lightfield rendering. Technical Report. Indiana University and Adobe Systems, 2008.
Lumsdaine, A.; Georgiev, T. The focused plenoptic camera. In: Proceedings of IEEE International Conference on Computational Photography, 1–8, 2009.
Dansereau, D. G.; Pizarro, O.; Williams, S. B. Decoding, calibration and rectification for lenseletbased plenoptic cameras. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 1027–1034, 2013.
Perwaβ, C.; Wietzke, L. Single lens 3D-camera with extended depth-of-field. In: Proceedings of SPIE 8291, Human Vision and Electronic Imaging XVII, 829108, 2012.
Bishop, T. E.; Favaro, P. Plenoptic depth estimation from multiple aliased views. In: Proceedings of IEEE 12th International Conference on Computer Vision Workshops, 1622–1629, 2009.
Levoy, M.; Hanrahan, P. Light field rendering. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, 31–42, 1996.
Wanner, S.; Fehr, J.; Jähne, B. Generating EPI representations of 4D light fields with a single lens focused plenoptic camera. In: Lecture Notes in Computer Science, Vol. 6938. Bebis, G.; Boyle, R.; Parvin, B. et al. Eds. Springer Berlin Heidelberg, 90–101, 2011.
Hahne, C.; Aggoun, A.; Haxha, S.; Velisavljevic, V.; Fernández, J. C. J. Light field geometry of a standard plenoptic camera. Optics Express Vol. 22, No. 22, 26659–26673, 2014.
Johannsen, O.; Heinze, C.; Goldluecke, B.; Perwaβ, C. On the calibration of focused plenoptic cameras. In: Lecture Notes in Computer Science, Vol. 8200. Grzegorzek, M.; Theobalt, C.; Koch, R.; Kolb, A. Eds. Springer Berlin Heidelberg, 302–317, 2013.
Georgiev, T.; Lumsdaine, A.; Goma, S. Plenoptic principal planes. Imaging Systems and Applications, OSA Technical Digest (CD), paper JTuD3, 2011.
Hahne, C.; Aggoun, A.; Velisavljevic, V. The refocusing distance of a standard plenoptic photograph. In: Proceedings of 3DTV-Conference: The True Vision—Capture, Transmission and Display of 3D Video, 1–4, 2015.
Birklbauer, C.; Bimber, O. Panorama light-field imaging. Computer Graphics Forum Vol. 33, No. 2, 43–52, 2014.
Bok, Y.; Jeon, H.-G.; Kweon, I. S. Geometric calibration of micro-lens-based light-field cameras using line features. In: Lecture Notes in Computer Science, Vol. 8694. Fleet, D.; Pajdla, T.; Schiele, B.; Tuytelaars, T. Eds. Springer International Publishing, 47–61, 2014.
Thomason, C. M.; Thurow, B. S.; Fahringer, T. W. Calibration of a microlens array for a plenoptic camera. In: Proceedings of the 52nd Aerospace Sciences Meeting, AIAA SciTech, AIAA 2014-0396, 2014.
Zhang, Z. A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 22, No. 11, 1330–1334, 2000.
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, 3280–3287, 2013.
Sabater, N.; Drazic, V.; Seifi, M.; Sandri, G.; Perez, P. Light-field demultiplexing and disparity estimation. 2014. Available at https://hal.archivesouvertes.fr/hal-00925652/document.
Author information
Authors and Affiliations
Corresponding author
Additional information
This article is published with open access at Springerlink.com
Chunping Zhang received her B.E. degree from School of Computer Science, Northwestern Polytechnical University in 2014. She is now a M.D. student at School of Computer Science, Northwestern Polytechnical University. Her research interests include computational photography, and light field computing theory and application.
Zhe Ji received her B.E. degree in technology and computer science from Northwestern Ploytechnical University in 2015. She is now a M.D. student at School of Computer Science, Northwestern Polytechnical University. Her current research interests are computational photography, and light field computing theory and application.
Qing Wang is now a professor and Ph.D. tutor at School of Computer Science, Northwestern Polytechnical University. He graduated from the Department of Mathematics, Peking University in 1991. He then joined Northwestern Polytechnical University as a lecturer. In 1997 and 2000, he obtained his master and Ph.D. degrees from the Department of Computer Science and Engineering, Northwestern Polytechnical University, respectively. In 2006, he was awarded the Program for New Century Excellent Talents in University of Ministry of Education, China. He is now a member of IEEE and ACM. He is also a senior member of China Computer Federation (CCF).
He worked as research assistant and research scientist in the Department of Electronic and Information Engineering, the Hong Kong Polytechnic University from 1999 to 2002. He also worked as a visiting scholar at the School of Information Engineering, the University of Sydney, Australia, in 2003 and 2004. In 2009 and 2012, he visited the Human Computer Interaction Institute, Carnegie Mellon University, for six months and the Department of Computer Science, University of Delaware, for one month, respectively.
Professor Wang’s research interests include computer vision and computational photography, such as 3D structure and shape reconstruction, object detection, tracking and recognition in dynamic environment, and light field imaging and processing. He has published more than 100 papers in the international journals and conferences.
Open Access The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www. editorialmanager.com/cvmj.
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
About this article
Cite this article
Zhang, C., Ji, Z. & Wang, Q. Decoding and calibration method on focused plenoptic camera. Comp. Visual Media 2, 57–69 (2016). https://doi.org/10.1007/s41095-016-0040-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41095-016-0040-x