Abstract
Reprojection of texture issued from cameras on a mesh estimated from multi-view reconstruction is often the last stage of the pipeline, used for rendering, visualization, or simulation of new views. Errors or imprecisions in the recovered 3D geometry are particularly noticeable at this stage. Nevertheless, it is sometimes desirable to get a visually correct rendering in spite of the inaccuracy in the mesh, when correction of this mesh is not an option, for example if the origin of error in the stereo pipeline is unknown, or if the mesh is a visual hull. We propose to apply slight deformations to the data images to fit at best the fixed mesh. This is done by intersecting rays issued from corresponding interest points in different views, projecting the resulting 3D points on the mesh and reprojecting these points on the images. This provides a displacement vector at matched interest points in the images, from which an approximating full distortion vector field can be estimated by thin-plate splines. Using the distorted images as input in texturing algorithms can result in noticeably better rendering, as demonstrated here in several experiments.
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References
Atkinson, K. (ed.): Close Range Photogrammetry and Machine Vision. Whittles Publishing (2001)
Faugeras, O., Luong, Q.: The Geometry of Multiple Images. MIT Press, Cambridge (2001)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2003)
Ma, Y., Soatto, S., Koseck, J., Sastry, S.: An Invitation to 3-D Vision. Interdisciplinary Applied Mathematics, vol. 26. Springer, Heidelberg (2004)
Keriven, R., Faugeras, O.: Complete dense stereovision using level set methods. In: Burkhardt, H.-J., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1406, pp. 379–394. Springer, Heidelberg (1998)
Pons, J.P., Keriven, R., Faugeras, O.: Multi-view stereo reconstruction and scene flow estimation with a global image-based matching score. The International Journal of Computer Vision 72(2), 179–193 (2007)
Vu, H., Keriven, R., Labatut, P., Pons, J.P.: Towards high-resolution large-scale multi-view stereo. In: IEEE Conference on Computer Vision and Pattern Recognition (2009)
Furukawa, Y., Ponce, J.: Accurate, dense, and robust multiview stereopsis. In: IEEE Conference on Computer Vision and Pattern Recognition (2007)
Eisemann, M., De Decker, B., Magnor, M., Bekaert, P., de Aguiar, E., Ahmed, N., Theobalt, C., Sellent, A.: Floating Textures. Computer Graphics Forum (Proc. Eurographics EG 2008) 27(2), 409–418 (2008)
Tzur, Y., Tal, A.: Photogrammetric texture mapping using casual images. In: Proceedings of ACM SIGGRAPH (2009)
Quan, L., Tan, P., Zeng, G., Yuan, L., Wang, J., Kang, S.: Image-based plant modeling. In: Proceedings of ACM SIGGRAPH (2009)
Lowe, D.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. In: Proceedings of British Machine Vision Conference, vol. I, pp. 384–393 (2002)
Mikolajczyk, K., Tuytelaars, T., Schmid, C., Zisserman, A., Matas, J., Schaffalitzky, F., Kadir, T., Van Gool, L.: A comparison of affine region detectors. International Journal of Computer Vision 65 (2005)
Bookstein, F.: Principal warps: thin-plate splines and the decomposition of deformations. IEEE Trans. on PAMI 11(6), 567–585 (1989)
Wahba, G.: Spline Models for Observational Data. SIAM, Philadelphia (1990)
Golub, G., Van Loan, C.: Matrix Computations. Johns Hopkins University Press, Baltimore (1996)
Bernardini, F., Martin, I., Rushmeier, H.: High-quality texture reconstruction from multiple scans. IEEE Trans. on Visualization and Computer Graphics 7(4), 318–332 (2001)
Lempistky, V., Ivanov, D.: Seamless mosaicing of image-based texture maps. In: Proc. of ICCV (2007)
Burt, P., Adelson, E.: A multiresolution spline with application to image mosaics. ACM Trans. on Graphics 2(4), 217–236 (1983)
Allène, C., Pons, J.P., Keriven, R.: Seamless image-based texture atlases using multi-band blending. In: Proc. of ICPR, pp. 1–4 (2008)
White, R., Crane, K., Forsyth, D.: Capturing and animating occluded cloth. In: SIGGRAPH (2007)
Furukawa, Y., Ponce, J.: Dense patch models for motion capture from synchronized video streams. Technical report, Willow Technical report 02-07 (2007)
Franco, J.S., Boyer, E.: Exact polyhedral visual hulls. In: British Machine Vision Conference, vol. 1, pp. 329–338 (2003)
Kazhdan, M., Bolitho, M., Hoppe, H.: Poisson surface reconstruction. In: Eurographics Symposium on Geometry Processing, pp. 61–70 (2006)
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Aganj, E., Monasse, P., Keriven, R. (2010). Multi-view Texturing of Imprecise Mesh. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12304-7_44
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DOI: https://doi.org/10.1007/978-3-642-12304-7_44
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