Abstract
Light field cameras capture a scene’s multi-directional light field with one image, allowing the estimation of depth. In this paper, we introduce a fully automatic fast method for depth estimation from a single plenoptic image running a RANSAC-like algorithm for feature matching. The novelty about our approach is the global method to back project correspondences found using photometric similarity to obtain a 3D virtual point cloud. We then use lenses with different focal-lengths in a multiple depth map refining phase and their reprojection to the image plane, generating an accurate depth map per micro lens. Tests with simulations and real images are presented and show a good trade-off between computation time and accuracy of the method presented. Our method achieves an accuracy similar to the state-of-the-art in considerable less time (speedups of around 3 times).
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References
Bishop, T.E., Zanetti, S., Favaro, P.: Light field superresolution. In: Proceedings of IEEE International Conference on Computational Photography, ICCP, pp. 1–9 (2009)
Dansearau, D., Bruton, L.: Gradient-based depth estimation from 4D light field. In: Proceedings of International Symposium on Circuits and Systems, vol. 3, pp. III-549–552 (2004)
Fleischmann, O., Koch, R.: Lens-based depth estimation for multi-focus plenoptic cameras. In: Jiang, X., Hornegger, J., Koch, R. (eds.) GCPR 2014. LNCS, vol. 8753, pp. 410–420. Springer, Heidelberg (2014)
Ives, H.E.: Optical properties of Lippman lenticulated sheet. J. Opt. Soc. Am. 21, 171 (1930)
Liang, C.K., Ramamoorthi, R.: A light transport framework for lenslet light field cameras. ACM Trans. Graph. (TOG) 34(2), 16 (2015)
Lin, H., Chen, C., Bing Kang, S., Yu, J.: Depth recovery from light field using focal stack symmetry. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3451–3459 (2015)
Lippmann, G.: Épreuves réversibles. Photographies intégrals. C. R. Acad. Sci. 146, 446–451 (1908)
Lumsdaine, A., Georgiev, T.: Full resolution lightfield rendering. Indiana University and Adobe Systems, Technical report (2008)
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 hand-held plenoptic camera. Comput. Sci. Tech. Rep. CSTR 2(11), 1 (2005)
Perwass, C., Wietzke, L.: Single lens 3D-camera with extended depht-of-field. In: Proceedings of SPIE Human Vision and Electronic Imaging (2012)
Tao, M., Hadap, S., Malik, J., Ramamoorthi, R.: Depth from combining defocus and correspondence using light-field cameras. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 673–680 (2013)
Wang, T.C., Efros, A.A., Ramamoorthi, R.: Occlusion-aware depth estimation using light-field cameras. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3487–3495 (2015)
Wanner, S., Goldlueck, B.: Globally consistent depth labeling of 4D light fields. In: Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 41–48 (2012)
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Ferreira, R., Goncalves, N. (2016). Fast and Accurate Micro Lenses Depth Maps for Multi-focus Light Field Cameras. In: Rosenhahn, B., Andres, B. (eds) Pattern Recognition. GCPR 2016. Lecture Notes in Computer Science(), vol 9796. Springer, Cham. https://doi.org/10.1007/978-3-319-45886-1_25
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DOI: https://doi.org/10.1007/978-3-319-45886-1_25
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